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Q: What is a code sprint?
A code sprint is an accelerated research and development program, where we pair talented developers with senior researchers and engineers for 3-6 months of extended programming work. The model is inspired by the Google Summer Of Code initiative, and is meant to create open source solutions for interesting 2D/3D computer perception problems. Each code sprint is financially supported by a different institution (see below).
Code sprints are made possible through the involvement of our host organization, Open Perception. Please see our mission page for more information.
Q: What does this blog represent?
The Point Cloud Library (PCL) developer blog represents a great way to keep track of daily updates in PCL sponsored code sprints. Our developers are writing about their experiences and progress updates while working on exciting PCL projects.
The following shows the current list of ongoing code sprints. Click on any of the logos below to go to the respective sprint blog page.
The list of code sprints which have been completed is:
We would like to thank our financial sponsors for their generous support. For details on how to start a new code sprint or contribute to PCL, please visit http://www.pointclouds.org/about and our organization's web site at http://www.openperception.org/get-involved/.
- Introduction
Geometrical models of trees in the field of computational forestry are nowadays referred to as Quantitative Structure Models (QSMs). The capability of those models exceeds pure volume estimation of trees. If the volume of a tree is multiplied with density values the above ground biomass (AGB) of a tree can be derived non destructively.
Instead of being limited to predict the AGB like statistical or voxel based approaches QSMs give also insight into internal biomass distributions of a tree.
The geometrical building blocks of such models are commonly cylinders fitted into terrrestrial laser scan point clouds.
SimpleTree is an open source tool to build QSMs from TLS clouds (SimpleTree homepage). The released version is based on PCL 1.8.0.
- The cylinder fitting method
Typically cylinders are fitted into point clouds with either RANSAC or NLS fitting routines. NLS needs initial estimates of cylinder parameters. Also RANSAC tends to produce errourness cylinders, if no initial segmentation of the point cloud is performed before.
The method implemented in SimpleTree relies on search spheres to produce an initial tree model which is enriched afterwards. A sphere with its center point located on the tree skeleton with a radius larger than the underlying represented branch or stem segment will cut the point cloud. All points located on the epsilon neighbourhood of the sphere will represent one or more circular cross sectional areas.
Into this subpoint cloud a circle can be fitted with RANSAC (Module sample_consensus). The sphere center point, the circle center point and the circle radius serve as parameters of a preliminary detected cylinder.
If the circle is enlarged and transformed to a 3D sphere the procedure can be repeated recursively.
To get fast access to the epsilon neighbourhood of a sphere a PCL search structure (Module octree) is used. All points contained in a search sphere have to be removed as soon as the sphere is utilized to prevent the algorithm to jump back and forth infinitely. For the case the epsilon neighbourhood of a sphere contains multiple cross sectional areas - this occurs in branch junctions - a clustering (Module segmentation) has to be performed. Into each cluster a circle is fitted
the largest circle is processed first (marked in green), while the others are stored in a FIFO queue to be processed later (marked in yellow).
By the nature of the algorithm a detected cylinders end point will coincide with another cylinders start point and an informatics tree structure can be utilized to store the cylinders. Several non PCL related statistical post processing procedures will adjust the tree structure and the cylinder parameters. The fit quality is also improved by another RANSAC routine. Points are spatially allocated to their nearest cylinder and only on this sub group a 3D RANSAC cylinder fit is performed. Before cylinder RANSAC:
and after RANSAC:
The final models are highly accurate and the informatics tree structure allows extraction of diameter classes
or the extraction of tree components like stem and branches:
Other possible parameters to extract are described in Hackenberg et al. 2015b.
- Crown representation
Two comprehensive crown representations are also computed with PCL. The crown can be modelled as a convex hull (Module surface)
or a concave hull
Only the convex hull's volume is for now written in Output files.
- ICP to align cloud of different years
ICP (Module registration) can be used to allign scans of the same tree taken at different times, in the example one cloud represents the unprooned tree and the second cloud was taken after the prooning.
The initial allignment (semi automatic) is described in Hackenberg et al. 2015b.
- References
The figures are taken from two peer-reviewed publications presenting the method and the software:
Hackenberg, J.; Morhart, C.; Sheppard, J.; Spiecker, H.; Disney, M. Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description. Forests 2014, 5, 1069-1105.
Hackenberg, J.; Spiecker, H.; Calders, K.; Disney, M.; Raumonen, P. SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds. Forests 2015, 6, 4245-4294.
The Honda Research Institute code sprint was finished. All code was commited, the final report is attached below.
In this phase, the focus was to integrate the pcl::KinfuTracker class and the OpenCV libraries in order to provide better input clouds for the Rigid/Non-Rigid Registration methods and thus to obtain better results.
By using the pcl::KinfuTracker class, it was possible to obtain an almost full scan of the heads of the subjects like the ones presented below:
Using the pcl::KinfuTracker had the disadvantage that unwanted objects were also scanned during the procedure, however by using the cv::CascadeClassifier, the program was able to pin-point the position of the head and move the statisitcal model to a favorable position so that the Rigid Registration method could fully align the model. ( The sphere represents the center of the face)
Obtaining better input point-clouds, allowed to better analyze the efficiency of these types of registrations. As stated in the previous post, the accuracy of the result depends on the regularizing weight of the Non-Rigid Registration, however there is one more parameter to take into account. The training set of face meshes was registered on a ten times smaller scale than the PCL point clouds are stored in. Intuitively, this means that when the program reads the database it should register the values as ten times smaller, however the subjects used for testing this program did not have heads of exactly the same size.
Below, you have an example of what happens when the scale is not set right:
This result was obtained because, as it is presented in the folowing picture, the chin of the model was matched with the neck of the target, even though the rest of the face seems to be in position:
Once the scale was properly established the correct result was obtained:
Feature work
- A method should be implemented so that it would not be necessary to set the right scale, no matter what kind of person is being scanned (child/adult)
- The pcl::KinfuTracker class has not been officially released, thus further maintenance of the prgram is required
- The Registration methods presented so far have to be compared to other methods like the ones already implemented in PCL
- Introduction
Once we have the segmentation, and the functions to make the measures of the segmented candidates to objects, we need to create a example where we analyze all segments and we decide which ones are objects or not. Also the objects that have more similarities in the measures, we can classify into a category.
- FrameWork
This tutorial gives an example of to implementation of the algorithm present in:
"Andrej Karpathy and Stephen Miller, and Li Fei-Fei", "Object Discovery in 3D Scenes via Shape Analysis", "International Conference on Robotics and Automation (ICRA)", "2013"
As the autors said in the abstract: "We present a method for discovering object models from 3D meshes of indoor enviromments. Our algorithm first descomposes the scene into a set of candidate mesh segments and then ranks each segment according to its "objectness" a quality that distinguishes objects from clutter".
In this example we will make all the framework to obtain the segmented objects at first and then calculate some geometric measures to make a clasification of the "objectness of the segmented candidates. After that we save all the "good" (the segments that the algorithm think are a object) and the measures asociated to each object. This can be used by the Recurrence to improve the clasification of the objects.
We begin with the based graph segmentation that was explained before. We made a over-segmentation of the meshes. To obtain diferent segments for each scene. We need to make this segmentations in all scenes that we want tto use for Object Discovery.
After we have the segmentation, we need to select the object-like segmentes. For that we apply some test to discard the not correct segments.
-Min and Max number of points. If the segment dont have the engouh points or is really bigger, we discard this object.
-After we take a look about the shape, we made two test, one about the shape, if is really flat or thin we discard this segment. Also we look into the size in the 3 axes. If this size is under or over a threshold is also rejected the segment.
-The next test is about diferent geometrical measures. This meauses where explained in the second post of this blog. We compute all this measures for each segment and we store this value. This will be used in the next test.
-Due to, we make a over-segmentation with different thresholds, probably will have the same segment more than one time. For that we make another test for each scene. This test name non-max supresion consist in look into all the segments with a result of more than 80% for a intersection ove union. If they have more than this, we compare the value of the measures, the object with the hightst value of this measure is keep and the other is discarded.
This is the last test. Now we show the results for a couple of scenes.
Scene 1
Object-like segments presents in the scene
Object-like segments presents in the scene
We store for a great number of scenes, all the segments and measures for each segment. Finally in the next step we add another measure, the recurrence.
More snapshots of some final results from different scenes:
Last Step: Recurrence
We are going to compute the recurrence in the previous results. For that we need to have the results of the object discovery. This recurrence consist in analyze all the segments in all the scenes, because segments that are commonly found in other scenes are more likely to be an object rather than a segmentation artifact. For that in the paper explains that, that the best way to measure the distance between the top k most similar segments is to find the objects with a 25% of extent along principal directions in size and measure the euclidean distance between their normalized shape measures. This is the best option, taking care the computacion time. We can use in the case other approachs like icp, ransac or local descriptors, global descriptors. In this case, for all objects founded in the segmentation proccess from before, we are going to obtain this score and find the 10 most similar objects.
After aplying the Recurrence we show the next results:
1st Query for an object
This case is really good (the implementation works!!!), and make more easy to understand the paper. After all the work, we obtain a possible object in a scene ( a cup) also with the aid of all scenes, give us a measure quite confident to clasify this objects. How much big is the number of scenes, this score improves its quality. This means, more scenes more quality.
2st Query for an object
3st Query for an object
4st Query for an object
Finally I think that I accomplish the main goal of the GSoC program. That was implement the algorithm in the PCL format.
To use this program and to look into the tutorials to we need to wait to be acepted a possible pull request with the source code, the 2 class that I create into the PCL website and in the PCL library.
that's all folks!!!
P.S. I will update the post with links if I get the pull the request of the code that I created during GSoC.
This project aims at getting features for each surface patch and group them to gether based on a machine learning technique. I have been experimenting on the features that could represent the surface patches belonging to an object and how they relate with the inter and intra object surface patches. Below are some of them, with their description and plots.
For all the below analysis please look at the image below and the segments derived out of basic region growing which doesn't make use of RGB color and purely based on surface curvature.
ColorHistogram: Binning colors is pretty normal thing to get the appearance cues. But they can be done in two ways. One that captures the color channels independently and the other that captures a dependent binning. In this section I am showing the independent binning of values on three different channels. Independent means at a pixel/point in scene we check RGB values different and increment the bin where these values belong to. Below is the plot that shows how the histograms look like for RGB and HSV color space.
ColorHistogram 3D: Binning colors dependently means having a matrix with RGB in 3 dimensions and increment the value of the (r, g, b) bin only if that combination is satified. This gives a 3D histogram. Below images show the 3D histogram concatenated to a 1D histogram for RGB, HSV and YUV color space. This binning style is referred from [1].
Verticality: Verticality actually represents how the surface patch is orientated with respect to the camera viewpoint. Histogram is developed by binning the difference of angles between the normals and the direction in which the camera is pointing to (i.e the positive z axis for any point cloud from Kinect). Below is the histogram plot for this feature. However this is not so useful to this segmentation project but more aimed towards the object discovery and saliency related problems to distinguish the a surface patch from its peers. This is implemented based on [2] which was adopted from [3].
Dimentionality Compactness: This actually shows how compact a surface patch is. One could do a PCA of a surface patch and derive a local frame of reference. This when followed by creating a bounding box gives the 3 dimensions in which the patch ranges the max. This bounding box will have 3 dimensions and their ranges are computed. Once this ranges (xrange, yrange, zrange) are sorted into min_range, mid_range and max_range, two ratios are computed. 1) min_range / max_range and 2) mid_range / max_range. Below is plot of this histogram for the above mentioned segments. This is implemented based on [2] which was adopted from [3].
Perspective scores: This is the ratio of the area projected in the image to the maximum area spread by the region in 3D. The pixel_range below means the bounding box range in the particular direction of the image pixels. xrange, yrange and zrange are the dimentions of the 3D bounding box of the surface patch. Note that PCA shouldn't done here as we are comparing the 3D surface patch with its appearance on the image. This is implemented based on [2] which was adopted from [3]. Below are the elements of the histogram.
pixel_x_range (in meters) / xrange
pixel_x_range (in meters) / yrange
pixel_x_range (in meters) / zrange
pixel_y_range (in meters) / xrange
pixel_y_range (in meters) / yrange
pixel_y_range (in meters) / zrange
diameter_of_bounding_box_pixels (in meters)/ diameter_of_cuboid_bounding_box_in_3d
area_of_bounding_box (in metersquare) / area_of_the_largest_two_dimentions_in_3d
Contour Compactness:
This is the ratio of the perimeter to the area of the region. This is the ratio of number of boundary points computed for a segment to the total number of points in the region. This is implemented based on [2] which was adopted from [3].
[1] A.Richtsfeld, T. Mörwald, J. Prankl, M. Zillich and M. Vincze: Learning of Perceptual Grouping for Object Segmentation on RGB-D Data; Journal of Visual Communication and Image Representation (JVCI), Special Issue on Visual Understanding and Applications with RGB-D Cameras, July 2013.
[2] Karthik Desingh, K Madhava Krishna, Deepu Rajan, C V Jawahar, "Depth really Matters: Improving Visual Salient Region Detection with Depth", BMVC 2013.
[3] Alvaro Collet Romea, Siddhartha Srinivasa, and Martial Hebert, "Structure Discovery in Multi-modal Data : a Region-based Approach", ICRA 2011.
These features will go into the features module of the pcl_trunk pretty soon. Currently working on the relational features which tells how two surfaces are related to each other. Next blog post should be on that.
Almost close to the end stage of GSoC, but this project has long way to go! Hope to keep pushing stuff till the entire pipeline is up on PCL.
I finished the work on the shape generator module. It became quite a versatile tool. Here is an overview what one can do:
Here are some examples how we can create a table top scenario consisting of a table, a cup on top and a saw which cuts into the table using recipes (shown on the right side). First we make and compile a recipe file for a table leg:
Next we will combine four legs plus a cylindrical plate to a full table (we set the variable Label to keep, which preserves different labels for the object's parts):
If we set Label to unique it will tell the generator to give only the table parts unique labels (not the parts the parts consist of :) )
This labeling would make sense if you want to test for instance part segmentation algorithms like LCCP.
Now let us combine the table and two objects. We have multiple options for the labeling now: First: Each object gets its own label:
Second: Give the parts of the objects their own label:
Or keep the labels of the parts and parts of parts unique :) :
Just to mention: All points have normal information attached:
Initially, the main objective of my project was to quickly obtain skeleton information using the GPU People module and focus the construction of the classification framework to recognize human actions. As it turned out that strong modifications of the gpu/people module were necessary in order to obtain the desired output of skeleton positions, the main direction of this project has moved more to extending and improving the gpu/people module. In the end, a simple action recognition framework was implemented, using K-Nearest-Neirghbour classifier on the positions and angles of selected joints, and RGB-D data of people performing the defined actions was collected for training.
The project had following major contributions:
- Calculation of the skeleton joint positions and their visualization (in the new People App the skeleton is visualized by default)
- Using Ground Plane People Detector in order to segment the body before the body labeling is applied. Without this modifications, the pose detector has big problems with large surfaces (walls, floor ...) and works robustly only in near-range. Besides this, the speed of the detector is increased as most of the voxels obtain very high depth depth values
- Tracking of the skeleton joints (see my previous post). Alpa-Beta filter is applied on the measured joint positions.
- Offline skeleton detection from the recorded LZF files.
- Classification of skeleton data sequences with K-Nearest-Neighbours
The source code of the new version of the gpu/people module can be downloaded here: https://github.com/AlinaRoitberg/pcl/tree/master/gpu/people
Building the app requires PCL installation with GPU enabled. For more information, see the PCL information on compiling with GPU and the tutorial for the initial /gpu/people module
The new application can be executed in the same way as the initial PeopleApp, while new functions can be actuvated with folowing additional flags:
|<bool> activate the skeleton tracking
|<float> set tracking parameter
|<float> set tracking parameter
|<int> fps for replaying the lzf-files (default: 10)
|<path_to_svm_file> activates body segmentation
Tree files for people detection: https://github.com/PointCloudLibrary/data/tree/master/people/results
SVM file for body segmentation (Ground Plane People Detector): https://github.com/PointCloudLibrary/pcl/tree/master/people/data
Example of execution (active segmentation, no tracking, using live data):
./pcl_people_app -numTrees 3 -tree0 ../tree_files/tree_20.txt -tree1 ../tree_files//tree_20_1.txt -tree2 ../tree_files/tree_20_2.txt -segment_people ../svm_path/trainedLinearSVMForPeopleDetectionWithHOG.yaml
Example of execution (active segmentation and tracking, using recorded PCLZF data)
./pcl_people_app -numTrees 3 -tree0 ../tree_files/tree_20.txt -tree1 ../tree_files//tree_20_1.txt -tree2 ../tree_files/tree_20_2.txt -segment_people ../svm_path/trainedLinearSVMForPeopleDetectionWithHOG.yaml -lzf /path_to_lzf_files/ -lzf_fps 10 -tracking 1
Take a look at the video demonstrating the modifications of the skeleton tracker (sorry for the format:) ): http://youtu.be/GhCrK3zjre0
Joint tracking
Although the body segmentation has solved the problems with full body visibility the resulting joint positions were still not sufficient. Besides the Gaussian noise, big "jumps" occured if suddenly a blob with a compeletly wrong position was labelled as the corresponding body part.
To solve this, I implemented a simple tracking function (Alpha-Beta-Filter) on top of the joint calculation. The filter estimates the new position based on the predicted (calculated from the previous position and velocity) and measured position. The weight of the measured position is given by the parameter alpha, while beta shows the weight of the velocity update.
Activation of tracking, alpha and beta parameters can be set in the PeopleApp.
The parameters should be chosen wisely, current default values worked good for me, but the also depend on the frame rate, which is not easily predictable, as it depends on the GPU.
Other changes to the skeleton calculation
Integration of tracking improved the results, however, problems still occured if the voxel labelling failed. Unfortunately, this happed a lot with the hands if they were very close to the rest of the body (and could be hardly distinguished).
That's why I added some correction based on the position of the elbows and the forearms. I estimate the expected position based on the positions of those body parts and if the measured position is too far away, the predicted result is used.
Besides I discovered the global variable AREA_THRES2 (in people_detector.cpp) and increasing it from 100 to 200 improved the labelling. Increasing it reduces the noise, while making the probability that small blobs (like hands) will be missed higher.
Data collection
As I have mentioned in my previous post, I wanted to collect the skeleton information from the recorded Kinect data in order to use the full framerate. To do so, I extended the people app with the option of using recorded PCLZF videos instead of the live Kinect data.
The positions of skeleton joints can be stored in a txt file with following flag: -w <bool val>
The data format is defined as following: SeqNumber Timestamp Pos1_x Pos1_y Pos1_z Pos2_x Pos2_y Pos2_z
I recorded the Kinect data of ten people performing the activities (defined in my previous post) multiple times. Afterwards I segmented the PCLZF-files with each directory containing the one execution of an action and run the people detector on each of them (I had a lot of fun with it:)). As copying the files and running the skeleton detector really took me "forever" I had to stick with a part of data and focus on the activity detection framework. The current framework contains segmented training data from 6 participants (269 recordings all together) and I will of course add the rest of the data, but I doubt that it would happen before the end of GSOC.
Another file format was defined for the training data, which includes all recorded skeletons, annotation of the action and UserID.
Classification Framework
I implemented a simple K-Nearest-Neighbours algorithm to classify a skeleton sequence. As all sequences have different lengths and the number of frames is high, one should find a way to calculate a good feature vector. In the implemented framework, classification happens in following way:
- Read skeleton data is divided into a fixed number of segments
- For each segment the joint positions are calculated as the mean value over all frames in the segment
- For each resulting skeleton (one per segment) further feature selection takes place: the decision which joint positions and angles to use
- All joint positions are calculated in relation to the Neck position (and not the sensor)
- The height of the person is estimated (difference between the head and the feet in the first or last segment) and the positions are normalized accordingly
- Mean and variance of each dimension of the feature vector is calculated over the whole training set and the data is normalized accordingly (this is important in KNN, to let all dimensions contribute in the same way).
- The feature vectors can be classified with K-NN (1-NN by default).
The application can classify a new sample as well as perform Leave-One-Out cross validation on the training set and print out the confusion matrix.
Currently I am getting following results:
The recognition rate of 34% might not sound that great. However one should consider the high number of actions and the fact that the skeleton data has some problems with joint positions, especially with the hands, which makes the recognition very challenging. The people detector also has some severe problems with unusual poses.
Further data processing, feature selection and more complex classification methods might improve the performance significantly in the future.
- Introduction
The implementation of the Efficient Graph-Based Segmentation, base on:Efficient Graph-Based Image Segmentation Pedro F. Felzenszwalb and Daniel P. Huttenlocher International Journal of Computer Vision, Volume 59, Number 2, September 2004
- Work
Due to license problems, I had to re-implement the code of the segmentation, also I need to implement the same code to use in Mesh and Point Clouds. To use in images, we need to create a graph, based on a image. To improve the results, In the paper recommend to smooth the image before the segmentation. I use the gauss filter implemented in PCL, for this purpose. After the code was written, and with the access to original code, I made some test to check if the segmentation was good.
The first test ,was about the segmentation without the gauss filter applied for each case and after, I made the same picture with the gauss filter .
- Results
Without Gauss Filter(Original Code)
As we can see in this image, there are a lot of segments, but if we compare this image with the next image, the adapted code is the same segments in both of them. The colors are different, because the colorization is generated random.
Without Gauss Filter(Adapted Code)
Then a test, with a sigma for the Gaussian filter of 0.5, and a threshold for the algorithm of 500 was made in the same image for both cases.
With Gauss Filter (Original Code)
With Gauss Filter (Adapted Code)
Here we can make that, there are some differences. After some research in the code. I found that, when we compute the weight for the graph, there are some minimal differences, this gives us the idea, that the smooth of the image, is different in both cases. Is small difference, some decimals, but this creates a different result. I didn't make more research about it, because is not part of the GSoC task.
- Point Cloud segmentation
Once we have the graph segmentation working, the next step is made the algorithm to use with Point Clouds. For that, the only thing that is needed to use, is create a new graph based on the difference of normal or curvature.
As we now, that the part of graph segmentation, we only need to check if the graph is generated correctly. For that I apply the segmentation to a mesh, and return the Point Cloud, this point cloud have some segments. Each segment have a unique color to see if it's correct.
The original mesh
The mesh segmented
The results are correct, this mesh have a lot of different objects, and this objects are well segmented, can be asociated for one possible object in the scene. Each of this objects, will be apply the diferent measures to test and discover if is a possible object or not.
In this post I will show you some results I got yesterday of our demo code working in a slightly cluttered scenario and fitting superquadrics to household objects.
Here is the environment we wish to recognize:
Here are the fitting results:
Here a bit more of detail with the colored pointclouds:
And here the fitted superquadrics alone for a better view:
The code used for the results shown in the rest of this post can be found here .
So, how does this code work? A general overview would go like this:
Things to figure out:
|Bohg, Jeannette, et al. "Mind the gap-robotic grasping under incomplete observation." Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE, 2011.
- Introduction
I begin with main part of the code, and probably the most easy to implement. In this part I write the code to make this measures for each Point Cloud. The input in the code is a point cloud (or set of pointclouds) and the output a vector with the values of the resultant measure. To simplify the code part and the use of this for other aplications,this part is separated from the segmentation, also if anyone want to use other segmentation that the proposed in the paper is usefull.
- "Objectnes measures"
We have 5 different measures:
- Compactness: This measure looks into how compact is a object. Search the minimum bounding sphere that contains all the surface of the mesh of the pointcloud.
- Symmetry: This measure analyze the reflective symmetry along the three principal axes, based on the eigenvalues of the scatter matrix.
- Smoothness: This measure evaluate the quality of the points of the segments, if the segments have points uniform spread around it, this will score high, if have spread points this will be have a low score.
- Local Convexity: This measure determine the convexity of each polygon edge in the mesh of the point cloud,and score each segment by the percentage of its edges which are convex.
- Global Convexity: This measure is generated by a convex hull, and after that a mean distance between the points and the convex hull isrecorded to create this measure.
- "Future Work"
In the future work, I need to implement the segmentation to give data to measure the objects and test this code.
Also, there is one measure missing, one that use all the segments in diferent scenes to make a better clasification.
This is the "recurence", but this depends on the on the number of scenes and segments, this need the segmentation before and analyze the number of similar segments in the objects in all scenes. Objects with similar segments should be in the same category.
Global Radius-based surface descriptor concatenates the RSD descriptor as discussed in the previous post to represent the complete object. GRSD gives a good description of the 3D shape of the object. Below are the set of objects and its GRSD descriptors i.e. histograms. I have used University of Washington's "Large scale RGBD dataset" for the experiments.
It can be seen that all the descriptors are different from eachother. Planes and box surfaces are similar as the surface characteristics are similar in this case. Both GRSD and RSD are pushed into the pcl-trunk for people to use. The test files for these two features are also included in the trunk for the basic usage of the same.
Currently working on the NURBS for small surface patches. Since NURBS are already available in PCL we will be looking at how to tailor the same for our needs. After this we plan to work on the features that compute the relationship between the surface patches.
- Introduction
The principal goal of this project will be implement the algorithm and app developed in:
-Fei-Fei, L., Karpathy, A., Miller, S."Object discovery Via Shape Analysis".
This automatic object discovery will be useful for robotics or autonomous vehicles and it will be able to find different class of objects. This new approach compares different parameters of an object to classify it into a class and diffence the objects. The parameters that defined a object is based on the: "Objectness measures" part in the paper. This is the core of the app and the most important part. And probably a good part to begin to code because is quite easy to code.
In the previous phase, it was presented how to obtain a statistical model from a set of face-meshes. The next step in our project is to "match" the mean face of the database, with the face of a random person, like the one in the picture below:
The matching is done by applying alternatively the following methods.
Rigid Registration
This method is very similar to the Iterative Closest Point Cloud algorithm, because the goal is to estimate a rotation matrix and a translation vector that would move the average face to an optimal position, near the face of the kinect. Basically, it is required to minimize the error and this is done by calculating the solution of this system in the least square sense. In order to calculate this solution, the system is first linearized using the Jacobian matrix.
Of course this process is applied iteratively, and below are presented a few stages of positioning of the model over the scan:
Non-Rigid Registration
Once the model is roughly aligned, we need to modify the shape of the model to match the face from the scan. For this we make use of the eigenvectors computed in the previous phase and we calculate the optimal solution of this system: , where is the matrix of eigenvectors, is the current form of the model and is the vector of basis coefficients that need to be determined.
However, there is on more constraint to be applied and that is to minimize the sum , where is the eigenvalue of the corresponding eigenvector. Therefore, to the Jacobian matrix of this system, we need to add a diagonal matrix with on the diagonal and multiplied by a certain weight.
The purpose of this regualrization is to determine to what degree the face should be deformed. The eigenvectors are stored in the matrix in decreasing order according to their eigenvalues and their position in this sorting order determines whether they have a greater or a smaller influence on the shaping of the model. When the model is mostly overlapping with the face in the scan, more information can be drawn about the final figure, hence the weight specified above should be smaller . On the other hand, if the model is not yet aligned with the scan, the deforming should be smaller and thus the weight should be bigger. Below you can see how the model looks for several values of the weight:
Notice that the shaping process tends to return the same effect if the weight of the regularizing constraint exceeds a certain value.
As mentioned above, these functions are applied alternatively for a few number of times, and the following results were obtained:
The above picture was obtained after one iteration and the following one after 10:
Also, below you can observe the precision of this method, the black figure representing the final version of the model and the green one representing the point cloud of the face:
The work on the lccp implementation is mainly done and the pull request is awaiting its approvel. Thanks a lot for the help of the pcl community (especially Sergey and Victor). Thanks to your comments the lccp algorithm is now in a much better shape. Talking about shapes: The next milestone in this GSOC project is the implementation of a shape generator which can be used to create various labeled scenes which can be used to create unit tests or benchmarks for part and/or object segmentation algorithms. I have written a big part of the code already. Now the question is: To which module of pcl should this generator go? I think about putting it into the geometry module. Any comment on this is more than welcome! The next image shows an assembled animal-like object which has been generated from simple geometric shapes (mainly geons).


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Medications to Treat Ankles
What you need to know about the many medications used for ankle problems.
Medications to ease pain, relieve inflammation, slow bone loss, modify the course of an inflammatory disease or prevent joint damage are an important part of treatment for many ankle problems. The medications used to treat arthritis and other problems that affect the ankles will depend largely on the form of arthritis or related condition you have. The types of medications commonly used in arthritis treatment are:
Nonsteroidal anti-inflammatory drugs. Including more than a dozen different drugs, some of which are available without a prescription, nonsteroidal anti-inflammatory drugs (NSAIDs) are used to help ease arthritis pain and inflammation. They are used for all forms of arthritis.
Corticosteroids. These quick-acting drugs, similar to the cortisone made by your own body, are used to control inflammation. If inflammation is due to a systemic inflammatory disease, your doctor may prescribe oral corticosteroids. If inflammation is limited to one or a few joints, your doctor may inject a corticosteroid preparation directly into the joint.
Analgesics. Analgesics are among the most commonly prescribed drugs for many forms of arthritis. They also may be used to relieve pain from ankle sprains, fractures and other injuries. Unlike NSAIDs, which target both pain and inflammation, analgesics are designed purely for pain relief. For that reason, they may be safe for people who are unable to take NSAIDs due to allergies or stomach problems, for example. When used as prescribed, they're also an appropriate, and possibly safer, choice for people whose arthritis causes pain but not inflammation.
If pain is in the soft tissues, you may find relief from an analgesic salve, rub or balm available over the counter under trade names such as Aspercreme, Ben-Gay, Capzasin-P, Eucalyptamint, Icy Hot, Voltaren Gel and Zostrix. These topical preparations work through a variety of active ingredients and may be helpful if you are unable to take oral medications, or if medications fail to relieve pain or reduce it to a manageable level.
Disease modifying anti-rheumatic drugs. Disease-modifying anti-rheumatic drugs (DMARDs) are drugs that work slowly to modify the course of inflammatory disease. Different DMARDs may be useful for a number of different forms of arthritis, including rheumatoid arthritis, lupus and psoriatic arthritis, all of which can affect the ankles.
Gout medications. Some medications for gout are designed to reduce levels of uric acid in the blood to help prevent future attacks of joint pain and inflammation. Others are designed to relieve the pain and inflammation of an acute attack. Many people with gout take both types of medication.
Biologic response modifiers. The newest category of medications used for rheumatoid arthritis and a few other inflammatory forms of arthritis are the biologic agents. There are currently eight such agents approved by the FDA. Each blocks a step in the inflammation process without suppressing the entire immune system. In addition to rheumatoid arthritis, certain biologic agents may be used in juvenile arthritis, ankylosing spondylitis and psoriatic arthritis.
Osteoporosis medications. Osteoporosis medications are those used to slow the loss of bone or help the body build new bone. Although they are not used specifically to treat ankles, strong bones are less prone to fracture. Osteoporotic ankle fractures are not common, but they can occur.
The Arthritis Foundation is the leading organization
providing support and funding research to improve the
lives of individuals with arthritis. You can help!

subset: commoncrawl


text: Find this wine Find this wine Whitehaven Sauvignon Blanc 2011 Delicious! Pin It Tweet 7 years ago by Hilary D. More posts Whitehaven Marlborough Sauvignon Blanc 2012 Lots of elderflower!!! Delicious! Anca had it at Thames oyster house in B'more 2013 6 years ago by Radudas Whitehaven Sauvignon Blanc 3 6 years ago by Rpenglish Whitehaven Marlorough Sauvignon Blanc 2012 Sauv Blanc wine class. Great with seafood. 6 years ago by Dana M. Whitehaven Marlborough Sauvignon Blanc 2012 Whitehaven Marlborough Sauv Blanc - $14.99 @ Modica in Seaside. Bright, citrus, fresh, beachy! Close behind Kim Crawford 6 years ago by Carin W. Whitehaven Marlborough Sauvignon Blanc 2012 Fabulous 6 years ago by Sabinaxiv


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EPN Breakfast- January 14, 2020 The Bourbon Barrel Connection: Revitalizing Appalachian Ohio economies and oak-dominated forests
co-hosted with the Ohio Department of Natural Resources (ODNR) Division of Forestry, will highlight the ... Department of Natural Resources (ODNR) Division of Forestry), and Dave Apsley (natural resources specialist, ... Program) will facilitate the audience Q&A session. Speakers: Dave Apsley, natural resources ...
News Release: Baldwin completes internship with Ohio State University Extension
and communities in the broad field of agriculture and natural resources. Students have the option to ...
News Release: Ritter completes internship with GC2 Ministries
communities in the broad field of agriculture and natural resources. Students have the option to specialize in ...
EPN Breakfast- December 4, 2019 Digging in with Ohio's Soil Experts
resource to meet the challenges of a changing climate. Ninety-five percent of our food comes from soil and ... Natural Resources will showcase an interactive, soil erosion simulator, demonstrating its use for ... Agriculture's Natural Resources Conservation Service in Ohio. He has served in this capacity since 2005, but ...
Ohio State University Extension Small Farm Program announces the 2020 Ohio New and Small Farm Colleges
budget, and where to find resources available for them if they chose to start a small farming operation. ... person, $100 for an additional family member. Along with the vast resources and knowledge gained, ... participants will receive a notebook (per each $150 registration) of all resource materials, a soil test, ...
Advising Resources
advisor, Katie Miller, should be your first point of contact for questions related to: Curriculum Resources ... with your academic advisor, EEDS students can find additional resources on the SENR advising website. ... Applied Economics flow chart and electives guide. Students can also connect with Academic Counselors in ...
Value of Recreation in Ohio 2019 Webinar
Ohio's natural land. The results illustrate that the natural landscape is an important resource in Ohio ... of the economy. Presenters: Jeremy Bruskotter, Professor, School of Environment and Natural Resources ...
Healthy Living Resources Telecasts
Healthy Living Resources is a new telecast series presented by Family and Consumer Sciences ...
EPN Breakfast- November 19, 2019. The Future of Wildlife Conservation: Funding Strategies for the State of Ohio
appointed by Mary Mertz, Director of the Ohio Department of Natural Resources, in January 2019 to be the ... served 8:10 a.m. Jeff Sharp, PhD. Director, School of Environment and Natural Resources provides welcome ... Resources. 10:00 a.m. Session 1 Topic: Wildlife access and engagement Access and engagement in ...
Converging on Wicked Systems Problems
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Even the Well-Off Find College Unaffordable Now
This WSJ story today on the rising cost of college for the affluent is a cavalcade of shocking statistics about our current student debt crisis: the average price of a four-year college has more than doubled in real terms since 1985; three million households owe $50k or more in student loans, a number that's tripled since 1989, inflation-adjusted. When even the golf course set can't afford college, you know we have a problem.
Of course, since the WSJ notes that "The upper-middle-income households now repaying student loans spend just 3.2% of their monthly incomes on debt payments," it's fair to say this is not the most pressing aspect of the Big Education bubble that will—just you wait—be popping, like a... nitrous balloon at a frat party, or some other college metaphor. Still, it's somewhat alarming to know that even the BMW-driving McMansion-livers are struggling to pay for Chad's four-year sports management degree at Notre Dame:
The Journal's analysis defined upper-middle-income households as those with annual incomes between the 80th and 95th percentiles of all households nationwide. Among this group, 25.6% had student-loan debt in 2010, up from 19.5% in 2007. For all households, the portion with student loan debt rose to 19.1% in 2010 from 15.2% in 2007.
The amount borrowed by upper-middle-income families, meanwhile, has soared. They owed an average of $32,869 in college loans in 2010, up from $26,639 in 2007, after adjusting for inflation, according to the Journal's analysis.
America's institutions of higher learning can sleep well at night that they, at last, were the thing that united the 99% and the 1%, in mutual despair.


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The 8th annual "Jimmy Kimmel Live: After the Oscars" special airs live on ABC SUNDAY, FEBRUARY 24 with guests including Academy Award(R) Winner Jamie Foxx, Channing Tatum and "Good Morning America" host Robin Roberts.
Last year "Jimmy Kimmel Live: After the Academy Awards" premiered a trailer for "Movie: The Movie" -- the biggest, most star-studded and spectacular non-existent film the world has ever seen. "Movie: The Movie" has garnered nearly 20 million views on YouTube alone to help make last year's post-Oscars special the most successful in "JKL" history.
This year Kimmel will debut the highly anticipated sequel, entitled "Movie: The Movie Twovie," starring Bradley Cooper, Jessica Chastain, Jude Law, Salma Hayek, John Krasinski, Samuel L. Jackson and many more. This promises to be the biggest, most star-studded imaginary film of all time.
Kimmel's previous post-Oscar specials have featured Oprah Winfrey, Tom Cruise, Ben Affleck, Robert Downey Jr., Matt Damon, Jon Stewart, Billy Crystal and Ellen DeGeneres.
"Jimmy Kimmel Live: After the Oscars" airs live on Oscar Sunday, February 24 from 12:05-1:05 a.m., ET after the late local news, and at 10:00 p.m., PT on ABC.
"JIMMY KIMMEL LIVE" (weeknights, 11:35 p.m., ET)
Jimmy Kimmel serves as host and executive producer of Emmy Award-nominated "Jimmy Kimmel Live," the ABC Television Network's late-night talk show. Now in its tenth season, "JKL" is packed with hilarious comedy bits and features a diverse lineup of guests including celebrities, athletes, musicians, comedians and humorous human interest subjects. Every night Kimmel delivers his up-to-the minute take on the latest news and pop culture topics from the day's events in his monologue, and has recently welcomed such notables as Johnny Depp, Meryl Streep, Tom Cruise, Robert Pattinson, Katy Perry, Will Farrell, Scarlett Johansson, Channing Tatum, Charlize Theron, John Krasinski, Jennifer Garner, Jessica Biel, Justin Bieber, Jessica Simpson, Kate Beckinsale, Ben Stiller, Jonah Hill, Andy Samberg, Michelle Williams, Zac Efron, Charlie Sheen, Chris Pine, Jeremy Renner, Jada Pinkett Smith, Josh Brolin, Russell Brand, Woody Harrelson and Joseph Gordon-Levitt.
"Jimmy Kimmel Live" broadcasts from Disney's El Capitan Theater, located on Hollywood Boulevard in the heart of L.A.'s star-studded Walk of Fame. Kimmel showcases this illustrious location's unique character throughout his show by regularly interacting with the local "Super Heroes" parading along the boulevard and challenging passersby to participate in various comedy bits. He has also created many one-of-a-kind concert experiences, closing down Hollywood streets around his studio to hold musical block party events with artists such as Coldplay, Lady Gaga, Jay-Z and Depeche Mode, as well as special outdoor and lobby performances by Adele, Linkin Park, Justin Timberlake, Drake, Tony Bennett, Pitbull, Britney Spears, Lady Antebellum, Usher, Lenny Kravitz, Brad Paisley, Lil Wayne, Phoenix, 50 Cent, No Doubt and Dave Matthews Band.
Jimmy Kimmel and Jill Leiderman serve as executive producers. Jason Schrift, Douglas DeLuca and Erin Irwin serve as co-executive producers. "Jimmy Kimmel Live" is shot live in front of a studio audience and produced by Jackhole Industries in association with ABC Studios. For more go to www.jimmykimmellive.com; also a "Jimmy Kimmel Live" app is available via iTunes.
"Jimmy Kimmel Live: After the Oscars" carries a TV-14,D,L,V parental guideline.


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Kids love to snack, but choosing healthy, nutritious options -- that they'll actually eat -- can be a challenge. Here are our suggestions for fun and easy ideas for after school, after dinner, or anytime they're hungry.
Children (and adults) of all ages will love this whimsical twist on sophisticated sushi, complete with a sweet sauce for dipping. Makes 4 servings (273 calories each).
Puree 1 1/2 cups low-fat buttermilk, 1 banana, 1 1/2 cups fresh or frozen berries, and 1/4 cup honey or agave syrup in a blender until smooth. Pour mixture into ice pop molds and freeze. Makes 10 pops (75 calories each).
Kids will love the color of this unusual gelato, made in part with fat-free milk. Makes 4 servings (166 calories).
Introduce your kids to protein-packed edamame: They'll have fun sucking the salty seeds out of their pods. Makes 4 servings (70 calories each).
Frozen mango lends this smoothie its sweetness and smooth texture while adding vitamins B6, C, and E. Makes one 8-ounce smoothie (52 calories).
A fun twist on a warm-weather classic gives this not-too-sweet treat a beautiful presentation. Makes 4 servings (130 calories each).
This shortbread calls for a combination of whole-wheat and traditional flour, and is rich in heart-healthy omega-3 fatty acids. Makes 16 servings (178 calories each).
These open-faced sandwiches serve up a grown-up taste in kid-size portions (32 calories per slice).
This dough is excellent with mix-ins such as nuts, chocolate, or fennel seed; experiment to find your favorite. And get the kids involved -- forming the twisty shape is a fun activity for little helpers. Makes 8 pretzels (202 calories each).
Making these cookies is a perfect family activity -- the absence of flour means there's no fuss and no mess, and they're safe even for family members with celiac disease or gluten intolerance. Makes 24 cookies (228 calories each).
A perfect gift for someone you love: Rolled oats and whole-wheat flour give these sweet treats added fiber. Makes 30 sandwich cookies (208 calories for 2).
When the kids cry for candy, keep them happy with these colorful, all-natural treats. Serve them as a sweet finish to a meal, or dip them in chocolate, let set, and pack them as a gift (155 calories per 1/4 cup serving).
You can't go wrong with pizza -- and topping it with yellow pepper is a great way to get children used to eating vegetables. Whole-wheat pita bread forms the crust for these wedges topped with mozzarella and homemade tomato sauce. Makes 48 wedges (24 calories each).
Who wants boring old yellow chips when you can have bright red ones? To create thin, evenly sliced beets, use a mandoline slicer -- plastic models are available at housewares stores. Makes 4 servings (47 calories each).
A familiar fruit salad is a great way to introduce kids to exotic flavors like ginger and coconut. Makes 4 servings (299 calories each).
This drink makes a refreshing and nutritious snack -- especially once you swirl in fresh fruit. Makes 4 shakes (188 calories each).
Worcestershire sauce, Tabasco sauce, and Old Bay seasonings give rice and corn cereal a delicious kick. The ingredients may sound grown up, but when all combined, kids can't resist! Makes 12 cups (171 calories per 1/2 cup serving).
This creamy shake derives its deep flavor and color from blackberries, rich in vitamin C, mixed with a few spoonfuls of honey. Ground cardamom provides a counter-balance to the sweetness. Makes 4 servings (158 calories each).
Instead of using regular cookies as the "bread" for ice cream sandwiches, use thin and crispy low-cal waffle cookies (166 calories each, with vanilla ice cream).
For breakfast or an afternoon snack, an egg provides protein and healthy fat. Get kids to eat their veggies with a cleverly constructed bell-pepper border. Makes 4 servings (189 calories each).
Adventurous children will be delighted by flavors in this sorbet, made with red papaya and a zingy dose of freshly squeezed lime juice. Makes 4 servings (221 calories each).
These cupcakes use orange marmalade, a citrus preserve that includes shreds or chunks of the peel, as an ingredient and a topping. If you find it too bitter, look for "sweet" on the label or purchase marmalade made from sweet oranges. Makes 18 cupcakes (237 calories each).
This delightful summer slushie blends bananas, pineapple, orange and lemon juice, and sugar. Lemon-lime soda and mint sprigs are optional. Makes 6 servings (165 calories each).
These swirly snack bars can be refrigerated, covered with plastic wrap or foil, for up to two days. Makes 24 bars (202 calories each).
Have fun making sweet, flavorful swirls when you pour this mixture into their ice-pop molds. Makes 10 pops (59 calories each).
You don't need a campfire to create a summer-camp vibe -- any outdoor grill will do. Makes 4 s'mores (117 calories each).
These cookies are quick and easy to make, using not-too-sweet, store-bought chocolate wafers. Makes 16 cookies (80 calories each).
Zucchini makes these treats nice and moist. You can substitute pecans for the walnuts, and serve them instead of high-calorie cupcakes. Makes 24 muffins (176 calories each).
These pretty pink sandwiches look especially nice dusted with confectioners' sugar. Makes 15 pies (240 calories each).
With leaner ground sirloin, the sliders have less fat and the rolls won't get soggy. Makes 8 sandwiches (189 calories each).
Spoil the kids for special occasions -- without feeling guilty about it -- with brownies made with whole-wheat flour and unsweetened applesauce, topped with frozen yogurt. Makes 8 sundaes (275 calories each, without extra toppings).
This sweet and crunchy afternoon snack can be ready in five minutes. Makes 6 servings (108 calories each).
Kids and adults will both love these tiny, savory tuna-topped crackers. Makes 16 mini melts (20 calories each).
Using assorted dried fruit adds a colorful twist to this classic after-school snack. Makes 2 servings (102 calories each).
This anytime snack can be stored at room temperature for up to a month. Makes 6 servings (322 calories each).
Rich in fiber and heart-healthy omega-3s, this recipe has 20 percent to 30 percent fewer calories and 30 percent to 60 percent less fat than most store-bought brands. Makes two cups (194 calories per serving).
Instead of dousing popcorn in butter, season plain kernels with chili powder, lime, and coarse salt. The movie-night snack will be just as tasty but lower in calories -- and cholesterol-free. Makes eight 1-cup servings (58 calories each).
A coating of toasted almonds and coconut around these inventive rice pudding balls keeps them from sticking to your fingers, and adds a satisfying crunch. Makes about 24 balls (95 calories each).
A healthy redo of French fries, this popular "vegetable" curbs the fat and sodium but keeps the crunch and flavor. Makes 4 to 6 servings (167 calories each).
Dates and applesauce -- full of fiber, vitamins, and natural sugars -- create a complex caramel flavor when combined with honey (50 calories each).
The nutritional value of traditional chocolate chip cookies is upped by using bittersweet dark chocolate, oat flour, brown rice syrup, and natural almonds. Makes 4 dozen cookies (104 calories each).
The secret ingredients in these brownies-made-healthier are whole-wheat flour and sweet potato puree. Makes 12 brownies (148 calories each).
This dairy-free cocoa will keep the kids warm on cold winter days. Makes 4 servings (327 calories each).
This year, don't reach for powdered ginger. Fresh ginger gives this traditional dessert a healthy, flavorful update. Makes 12 servings (252 calories each).
Our pomegranate gelee replaces gelatin with agar, a natural setting agent made from seaweed. Makes 8 servings (157 calories each).
Pizza for dessert! Ricotta holds the berries in place while providing a wonderfully creamy texture and slightly sweet flavor. Makes 4 servings (282 calories per serving).
Kanten, also called agar-agar, is a vegetable gelatin. This dish is a great alternative to store-bought cups of the jiggly stuff. Makes 6 to 8 servings (about 175 calories each).
Nonfat frozen yogurt and egg whites lighten up this indulgent ice cream cookie. Makes 12 sandwiches (90 calories each).


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Construction of new facilities by data center operators has many U.S. regions grappling with massive new demands for electric infrastructure. Space, cooling, and energy-capacity issues faced by existing data centers have compounded the problem. To address these challenges, a nationwide coalition of utilities has been formed to discuss and coordinate energy efficiency programs for the high-tech industry, with a focus on data centers.
San Francisco-based Pacific Gas & Electric (PG&E) is leading the coalition formation. "We have developed program and service offerings for the information technology industry, and sharing our knowledge with other utilities will drive energy-savings and environmental benefits more widely in this rapidly expanding market," says Roland Risser, director of customer energy efficiency for PG&E.
PG&E's program and service offerings for the high-tech sector include financial incentives for customers who pursue energy-efficiency projects in their data centers. According to the company, it was among the first to offer incentives for virtualizations and server consolidation — a program that is prompting customers to remove underused computing equipment using virtualization technology.
Because data centers may use up to 100 times the energy per square foot of typical office space, energy-efficiency programs are crucial. Programs like the ones offered by PG&E can help customers live within their existing data centers as well as limit the energy impact of new ones.
To date, the Northwest Energy Efficiency Alliance (NEEA), Portland, Ore.; TXU Energy, Dallas; Austin Energy, Austin, Texas; New York State Energy Research and Development Authority (NYSERDA), Albany, N.Y.; and NSTAR, Westwood, Mass., have joined the coalition.
"The Northwest is experiencing substantial growth in data centers, with new facilities recently constructed or announced by Google, Microsoft, Yahoo, and others," says Stacey Hobart, NEEA manager of corporate marketing and communications. "The electric load represented by these facilities is significant, and it is in everyone's best interest to build-in as much efficiency as possible."


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Teacher resources and professional development across the curriculum
Teacher professional development and classroom resources across the curriculum
Dealing with Controversial Issues
How provocative should social studies topics be?
Some educators believe that certain issues are best addressed privately -- at home, for example -- and that social studies should focus on objective facts. Others argue that public controversy is characteristic of a healthy democracy and that working with others to address multiple perspectives is a skill that students need to develop in a classroom context.
All social studies teachers must inevitably deal with controversial issues, ranging from basic ideas of fairness and equality in a democracy, to immigration, to the distribution of world resources. Controversial issues require students to conduct thorough research, master concepts on both sides of an issue, and develop a perspective of their own.
The most difficult issues often have a profound impact on students, and class discussions about these issues can leave teachers feeling like referees. However, in a democracy it is critical for students to learn how to listen to opposing viewpoints, and the teacher's role must be to create an open forum that allows opposing viewpoints to be fully expressed. The challenge for all teachers is finding the fine line between engaging students' interest and maintaining a sense of objectivity that lets students master the material and develop their own perspectives.
© Annenberg Foundation 2017. All rights reserved. Legal Policy


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WASHINGTON (EWTN News/CNA)—The U.S. House of Representatives passed legislation on Oct. 13 that would prevent federal taxpayer funding of abortion under President Obama's health-care law. The approved measure would also strengthen conscience protection for health-care employees.
"A ban on taxpayer funding of abortion is the will of the American people and ought to be the law of the land," said House Speaker John Boehner, R-Ohio, on the House floor.
"But the law, particularly as it is currently enforced, does not reflect the will of the people. This has created additional uncertainty, given that Americans are concerned not just about how much we're spending, but how we're spending it."
H.R. 358, the Protect Life Act, passed by a vote of 251-172 in the House.
The bill makes certain that "the Hyde Amendment applies to all the programs that are both authorized and appropriated in Obamacare," said Rep. Chris Smith, R-N.J., during the debate over the act.
The Hyde Amendment is a provision added annually to appropriations bills providing federal funds for health care. It prohibits federal funding for abortions, except in the cases of rape, incest or to save the life of the mother.
"Nothing less than a comprehensive prohibition on public funding, promotion and facilitation of elective abortion in any federal health program satisfies the demands of social justice," said Smith.
The Protect Life Act also specifies that health-insurance carriers cannot be forced to cover abortion and protects the conscience rights of health-care individuals and institutions who refuse to participate in abortions.
The U.S. bishops applauded the passage of the bill.
"By passing the Protect Life Act, the House has taken an important step toward authentic health-care reform that respects the dignity of all, from conception onward," said Deirdre McQuade, pro-life spokeswoman for the U.S. Conference of Catholic Bishops.
The bill is expected to face heavy opposition in the Senate, and the Obama administration has threatened to veto the measure. A statement released by the administration on Oct. 12 said that "the legislation intrudes on women's reproductive freedom and access to health care and unnecessarily restricts the private-insurance choices that women and their families have today."
On Sep. 9, 2009, President Obama told Congress that under his legislation, "no federal dollars will be used to fund abortions, and federal conscience laws will remain in place."
The administration claims that the Affordable Care Act, along with an executive order issued by President Obama in March 2010, already prohibit federal funding of abortion, except in limited cases.
However, critics contend that the language of the act does not prohibit such funding. They argue that the president's executive order is inadequate because it does not amend the bill and would be overturned if brought to federal court.
The Obama administration criticized the Protect Life Act, saying that it "goes well beyond the safeguards found in current law and reinforced in the president's executive order by restricting women's private-insurance choices."
If the bill is passed by Congress, the president's "senior advisors would recommend that he veto" it, the Oct. 12 statement said.


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The yellow, house-like structure of the Ocilla-Irwin County Chamber of Commerce symbolizes the friendly atmosphere inside! Stop in to get all the information you need about Ocilla and Irwin County, including what is being done to promote economic growth to better the lives of Irwin County Citizens. We invite you to join us.
Farming income in Irwin County comes from poultry and eggs, row and forage crops, livestock and aquaculture, forestry and timber products, vegetables, ornamental horticulture, and fruits and nuts. Farm income in Irwin County in 2011 was $109 million.
Although we aim to serve the community with the latest technologies, Ocilla, Georgia remains a charm of the old south, where families come together and memories are made.Explore Resources
We may be a small town, but we have a lot going on. The annual Sweet Potato Festival, ribbon cuttings, meetings, social activities and more. Check the calendar and Save The Date!Check the Calendar


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Louis Daignault (ISN)
July 6, 2013, STARE JABLONKI, Poland (ISN) – Ben Saxton of Calgary and Chaim Schalk of Red Deer, Alta., continued a remarkable trend for Canadian beach volleyball on Saturday placing fifth at the FIVB World Championships.
The first-year Canadian pair opened the day upsetting sixth-seeds Janis Smedins and Aleksandrs Samoilovs of Latvia 21-15, 21-18 in the round of 16. The Latvians were one of the hottest teams coming into the worlds with two silvers and a victory at the last three FIVB World Tour stops.
A couple of hours later n the quarterfinals, Saxton and Schalk faced second-seeds and Olympic silver medallists Alison Cerutti and Emanuel Rego of Brazil and provided another tough battle falling 21-17 22-20.
This is the third straight strong result for Canada at an FIVB world championship this season. At the FIVB U21 World Championships two weeks ago, Grant O'Gorman of Toronto and Aaron Nusbaum of Aurora, Ont., won the silver. In May, Taylor Pischke of Winnipeg and Melissa Humana-Paredes of Toronto earned the bronze at the FIVB U23 World Championships.
The performance also continued a strong season for Saxton and Schalk. They opened 2013 with two bronze medals on the NORCECA (North and Central America and Caribbean) circuit, were fifth at the FIVB World Cup and posted two 17th place finishes on the World Tour.
Full results: www.fivb.org


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8' X 6' Run w/ 4' X 4' Modern Barn Coop (COMPLETE PACKAGE)
- 14 Gauge Powder Coated Steel Run
- Steel Frame Construction Coop and Run
- Fully Insulated Interior Coop
- All-Weather, Exterior Coop Siding
- Large Coop and Run Access Doors
- Removable Tray for Easy Cleaning
- Predator Resistant Metal Roofing
- Easy Assembly
- Houses Up To 16 Birds
- COOP: 4' L x 4' W x 6' H
- RUN: 6' L x 8' W x 5' H
- COOP: 425 lbs.
- RUN + ROOF: 170 lbs.
- 4' X 4' Classic Barn Chicken Coop
- 8' X 6' Complete Chicken Run
- (1) 4' Door Panel + (2) 6' Panels + (1) 8' Panel
- Complete Predator Digging Prevention
- (4) 4' + (2) 6' + (1) 8' Predator Digging Prevention Bars
- Hard Roofing for Coop & Run
- Skip-a-Day Silo Feeder Options Available
- Skip-a-Day Silo Waterer
- (4) Large Plastic Nesting Boxes
- (5) 4' Roosting Bars
- Chicken Coop Ramp
- Large 30 lb. Capacity Chicken Feed Storage Bin with Attachable Rack -OR-
- Hanging Chicken Coop Light W/ 2-Outlet Timer
- Add up to Two Coop Windows
- Feeder & Waterer Upgrades
- One Year Manufacturer's Warranty
- Accessories ship for free with this Complete package
The Chicken Condos 4' X 4' Modern Barn Chicken Coop with 8' X 6' Complete Run is a tremendous value and includes just about everything one could possibly need to keep their chickens safe, sound, and secure. Our 14 gauge Powder Coated Steel panels provide unmatched protection against predators of all stripes, especially when coupled with the included Corrugated Metal Roofing and Predator Digging Prevention System. You will be able to rest easy with the knowledge that your flock is well protected! This Complete package also includes our 4' X 4' Modern Barn Coop, which features steel-frame construction, warm, fully insulated interior and an all-weather wood exterior siding that not only looks great, but will last for years to come!
If it seems like we have thought of everything to keep your chickens safe and happy; you're right! But, it does not end there. We are also keeping you in mind! We all love raising our backyard chickens, but maintaining your coop can be time consuming and inconvenient, so we have done everything we can to make things easier! From our large coop access door, to our large run access door, to our removable tray for easy cleaning to our Skip-A-Day Feeding and Watering systems, this Complete Coop and Run package truly covers all bases! We are so excited about this package that we are also including several free gifts as a thank you for shopping with us! And remember, additional accessories will ship for free with this coop purchase! Still have questions? Give us a call at 1-877-527-3455 and our friendly staff will be more than happy to assist you!
Links to Included Items: Predator Prevention System, Silo Feeder, Silo Waterer, Large Plastic Nesting Boxes, Roosting Bars, Chicken Coop Ramp, Chicken Feed Storage Bin with Rack, Hanging Coop Light, Dual Outlet Timer, 4' X 4' Classic Barn Coop
Links to Optional Upgrades: Coop Windows, Automatic Chicken Feeder, 11 lb. Hanging Plastic Feeder, Automatic Bird Fount, 3 Gallon Waterer, 3 Gallon Waterer with Heater


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Becoming a Student
Vernon College is focused on student success! Whether you are a high school graduate, seeking a career change, or wanting to enhance your current career, Vernon College is the place for you.
Paying for College
Where do I start? Vernon College offers you access to a number of financial aid options to help pay for school.
Degrees, Certificates, Courses
Choose Your Path to Success!
Business & Community
Vernon College is proud to be your community partner!
The Vernon College Concurrent Enrollment/Dual Credit Program is a cooperative partnership between a high school district, a private secondary school, or a home school and Vernon College. The program enables students who meet entrance requirements to earn college credits while completing high school graduation requirements. Students who are approved by their individual high school (9th-12th grade) may take approved courses each academic semester (Academic Transfer or Career and Technical Education) for concurrent enrollment/dual credit. Students must meet TSI requirements for the courses they wish to enroll.
For further information contact:
Melissa Moore
Early College Start Coordinator
(940)696-8752 ext. 3303
Century City Center
4105 Maplewood Ave.
Wichita Falls, TX 76308
Copyright 2019 Vernon College


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20 Years of Storytelling
Studio B Films Inc is a full-service San Francisco Bay Area video production company and creative agency specializing in corporate, marketing, training, event, sizzle and web viral videos
Video Production Portfolio
Writing, Casting
Creative Brief
Technical Direction
Creative Direction
Client Services
Editing, Design
Online Strategy
Social Media
Video Distribution
Audience Reach
We want you to think of us as your in-house video production company and creative partner. Whether you need a web commercial, event sizzle video, corporate media communications, comedy, testimonial customer stories, explainer video, 3-D motion graphics or coverage of live events, Studio B Films will work with you to develop and produce engaging content that successfully connects with your audience.
The heart of what we do is story telling. And we've been hard at work since 1993, when independent filmmaker David Collier founded Studio B Films. David knows that producing award winning videos is a team sport so he pulled together an amazing group of producers, writers, directors, motion graphics artists, editors and music composers.
We work closely with your marketing department to help launch your company's products and differentiate you from your competitors. Lots of video production companies make pretty pictures. While we believe that's important, the special sauce we bring is our creativity, story telling and collaborative approach.
As a creative partner, a big part of our job is understanding your customer's pain points and decision-making process. We do more than just remove friction from the buying process. It's our mission to inspire and create an emotional connection.
We guide our clients through the process from script writing and creative concepting through post production. Our first step is the discovery phase where our goal is to fully understand the objectives of the videos, the intended audience, and what will motivate and inspire that audience. During this phase we dive in to understand our clients company story, so that all of our messaging is in alignment with your brand.
Producing compelling videos for our clients is of utmost importance, but the experience during the process is equally important. The team at Studio B films cares deeply about customer service. We build long-term relationships with our clients.
Video Production Services – Client Testimonials
"When we hire Studio B Films to create an event video we have come to trust them to deliver an end creative product that exceeds our expectations. They are professional, flexible, diligent and good collaborators. They provide the whole package, with a well balanced staff and a great team of editors. Their offices in Berkeley are convenient, accessible, and always welcoming. Our end products are on target and they are a joy to work with."Sophia Larioque, Event Producer
Opts Ideas
"Studio B produced a launch video for Ekso Bionics' exoskeleton that instantly went viral and for good reason: Vision + direction + interviewing skills + lighting + editing = Success beyond our expectations. Everything about working with them was a pleasure and a professional experience."Beverly Millson, Missing Sock Public Relations
Ekso Bionics
"Everything was great! The videos are stunning, the team was really easy to work with. Really, it couldn't have been a better working relationship and the product is being so well received; your staff is brilliant and a pleasure to work with."Randy S. Hyde, Campaign Manager
San Francisco Symphony
"Our experience with Studio B was flawless—from creative concept to execution—the work was everything we wanted and more. We asked them to create a promotional video that was not only educational, but generated enthusiasm and excitement for a new product launch. They came through with a video that exceeded our expectations. The team was responsive to our requests, and every department collaborated with us to ensure this video was delivered on time and at the best quality. Jane, David, Aaron and the entire team embrace a friendly, down to earth approach that's both refreshing and professional. We won't hesitate to call Studio B for projects of this kind in the future."Stephen Baloguh
Ancestry.com DNA
"Studio B, That band of amazing misfits. We've produced literally hundreds of stratospherically successful motion graphics and live action videos together. From documentary films, demos and product tours, high end animated video, we even shot the first augmented reality music video together. They seriously kill every project we've ever thrown at them. It is an absolute pleasure working with such a talented and committed team. Their range and capabilities are extremely rare in a production agency. They have been a production partner of ours for years and will be for years to come."AJ Joseph Executive Creative Director - Adobe


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Watch CBSN Live
Twenty years after Sam Flynn disappears, his tech-savvy, 27-year-old son Kevin finds himself in the gaming world his father created.
Credit: Walt Disney Pictures
If the future pans out to be as it was depicted in this high-tech Tom Cruise film where criminals are caught before they even commit a crime, the world would be a better place.
Credit: Twentieth Century Fox
A boy who was arrested for writing a computer virus when he was a kid and his new (cool) hacker friends use their computer skills to out a corporate extortion conspiracy.
Credit: United Artists
Set in 2035 A.D., in this movie, robots work for humans. Now imagine if said robots go a little crazy and stop obeying their supposed codes of conduct.
This movie tells the story of how Facebook came to be - scandals, drama and all.
Credit: Columbia Pictures
Wealthy industrialist Tony Stark builds an armored suit and saves people. And, he's cocky about it.
Credit: Paramount Pictures
If sophisticated dream technology existed, would you use it to redeem yourself?
Credit: Warner Brothers Pictures
This end-of-the-world movie is set 250 years into the future when cars fly, aliens roam and evil arrives.
Credit: Gaumont
A computer programmer by day becomes a hacker by night, and questions what's real.
The cyborg who tried to kill Sarah Connor makes it his mission to protect her son, who is the future leader of the resistance.
Credit: Carolco Pictures
The prequel life of James Kirk and Spock to the cult TV series we've grown to know and love.
Credit: Paramount Pictures
Six super-smart Massachusetts Institute of Technology (MIT) students are trained to become card-counting experts and win millions in Las Vegas.
Awesomely bad, this movie follows the adventures of software engineer Angela Bennett as her identity is stolen via the Internet.
Heartbroken people undergo an experimental psychiatric procedure to erase memories about each other.
Credit: Focus Features
A teen goes back in time using a time machine invented by a mad scientist.
Credit: Universal Pictures
A man whose genetic make-up is "underclass" travels in space and takes on the identity of a more superior human.
Credit: Columbia Pictures
This movie was based on the true story of the ill-fated Apollo mission for the moon. An accident cripples their space shuttle.
Business rivals unknowingly meet in an AOL chat room and - spoiler alert! - fall in love.
This action-thriller follows a soldier who finds out he's part of a science project. And, it stars Jake Gyllenhaal.
Credit: Vendome Pictures
A cute robot that collects waste embarks on a mankind-saving space journey.
Credit: Pixar Animation Studios
A robot boy is manufactured, but he has feelings, unlike other robots.
A former insurance investigator avenges his wife's murder, but his memory has been damaged. He tattoos notes on himself and takes Polaroids to help him chronicle events.
Credit: Newmarket Capital Group
An experimental military robot transforms after it's struck by lightning and becomes self-aware and conscious.
Credit: David Foster Productions
When half of the world suffers from Nerve Attenuation Syndrome, Johnny Mnemonic is used to carry information via a memory chip in his brain.
Credit: TriStar Pictures
Filmmakers document a journey to meet a girl they found on the Internet. What unravels is shocking.
Credit: Supermache
Four die in New York City after logging onto www.feardot.com, and detectives try to get to the bottom of it.
Credit: MDP Worldwide
This technology spy movie is about a convicted hacker who works with bad guys who are trying to access government secrets locked inside a complicated computer system.
Credit: Jonathan Krane Group
Two teenage geeks somehow manufacture a hot chick with their computer. She gives their egos a boost.
Luke Skywalker meets Han Solo, Chewbacca, Ben Kenobi, C-3PO and R2-D2 - they all go to rescue Princess Leia from the Empire.
Credit: Lucasfilm
A computer programmer thinks he has landed his dream job only to find out his boss has a dirty secret.
Credit: Metro-Goldwyn-Mayer
This movie is about a man who's trying to discern real life and the dream world. It's not long until the viewer starts to feel like he or she is the character in the dream world.
Credit: Fox Searchlight Pictures
A cab driver becomes a hostage to a contract killer who uses an HP tablet.
Based on the very popular video game series, a female scientist teams up with a military squadron to save the planet and rid herself of an alien infection.
Credit: Chris Lee Productions
A state-of-the-art computer develops emotions after champagne is spilled on him.
Credit: Virgin
A group of nerdy outcasts start their own nerdy fraternity to do nerdy things.
Credit: Interscope Communications
A kid computer whiz gains access to a top-secret computer and the U.S. nuclear arsenal.
Credit: Metro-Goldwyn-Mayer
A thriller about computers? Who wouldn't want to see this movie, which also delves into espionage, cryptography and government secrets. Scandalous!
This (sort of funny) made-for-TV documentary follows the founders of Apple and Microsoft in their early days as they begin to build their empires.
Credit: Half Entertainment
Software engineers at the Initech office go a little nutty when their VP hires two consultants known as "the Bobs" to downsize the company.
This cyborg in a steel shell fights crime, but also becomes the target of a super-villain.
Credit: Onion PIctures
Eight talented candidates enter a windowless room to take a test. There's only one simple question - but there are lots of rules. They duke it out to find the smartest in the room.
Credit: Bedlam Productions
Four goofy scientists set up a shop in an old firehouse to fight ghosts and goblins.
Credit: Black Rhino Productions
After a student receives an electric shock, his brain turns into a computer and he remembers everything he reads.
Credit: Walt Disney Productions
A genius mathematician builds a supercomputer at home that understands existence.
Credit: Harvest Filmworks
Error-checking devices have an accidental side effect, and the trust of two men is tested.
Credit: TH!NKFilm
A gardener is made a genius through a computer science application and intelligence enhancing drugs. The scientist mastermind behind the project loses control.
Credit: Allied Vision
A social worker and an FBI agent experiment with new technology to enter the mind of a serial killer to locate a kidnap victim.
Credit: Avery Pix
A paraplegic marine goes to Pandora on a mission to gather intel and infiltrate the Na'vi people using an "avatar" identity.
Law enforcement develop a virtual reality entity from the personalities of 150 serial killers to train police officers.
A teen genius is accepted into a university where he's partnered up with a science club legend to develop a high-powered laser.
Credit: Delphi III Productions


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THREE-AXLE BUS limits have increased from 20 tonnes to 22 tonne, reflecting increasing average weight of passengers, the National Heavy Vehicle regulator has officially...+MORE
AUSTRALIAN bus manufacturer BCI debuted its new Citirider E electric bus at BusVic 2019, recently. Using the latest generation lithium-phosphate batteries that are around 10...+MORE
SPONSORED CONTENT: Telematics has been a buzzword in the transport industry for some time. But as pressure mounts from compliance officers and safety regulators to provide...+MORE
When launched a few years ago here in Australia, the Hino Poncho was a 'cute little bus' giving potential buyers something to think about. Years later with 'on demand' now in...+MORE
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0 review for 250-403 Questions & Answers
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I am not really fanatical about keeping my bike in mint condition. It's not that I don't care about the stuff I own, it's more that if I use something a lot, I expect that it is going to show signs of use. Also, I don't want to obsess over every little thing and that is why in the initial post to Globe about why I would be a good recipient for their Globe Experience Project, I stated that the first thing I would do if awarded a bike is scratch it.
I noticed recently that after only a few weeks of riding, more scratching has occurred through normal use. In this case, the brake and gear cables are rubbing away the paint on the front of the bike. Take a look:
This does not bother me at all, if however you have a new bike and want to avoid such wear a see a rather simple hack - just take some clear packaging tape and put it on your frame. Do you have issues with cable rub? If so, how have you dealt with it?


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This will be the last post at New York Mets Online. However, I am not giving up on writing about the Mets. Instead I have a new partner and we have a Web site which will blow this one away in terms of style, content and consistent posting.
What is this new Mets site and how will it be different?
Mets360.com will produce all original content. Our analysis may be based on a news item, but we are not in the news-breaking business. Why do exactly what a couple dozen sites and blogs are already doing?
Once a story breaks, we will provide a unique perspective that will originate from asking different questions, coming at the news from a different angle and setting the events in context. Instead of enduring through the suffocating norms that include a series of links to third-party sites or an excerpt from a previously published report, Mets360.com will develop and present stories in a thoughtful and uniquely engaging presentation.
So, we will not simply regurgitate news from other sources. We will not give you a doctoral dissertation when the team brings up a seventh reliever from Triple-A. Instead we will focus on the stories that impact the club in a big way. And while nearly every current Mets site looks like it was designed in 1984 on a 256 K Leading Edge, Mets360.com will have a professional, 21st Century appearance.
Who are the people behind the Web site?
Mets360.com is the brainchild of John Strubel and Brian Joura, two people who are first and foremost fans of the team. We know the pain of missing out on the playoffs on the last day of the season. We know the joy of a backup catcher hitting a game-winning home run to vault the team into the playoffs. We experienced the heartache of following The Worst Team Money Could Buy. We lived the thrill of October 25, 1986 and can tell you exactly where we when Mookie Wilson hit that ball.
We can go on with key moments, high and low, that we have experienced as Mets fans. The thrill of finding out that the team acquired Keith Hernandez, the disappointment that Tim Leary never made it big with the club, the laughter every time the cap fell off John Pacella's head and the club's numerous attempts to find a substance to keep it in place. We understand the pain when the club trades your favorite player, whether that player was Tom Seaver or Duffy Dyer.
But not only do we have memories forged over a lifetime of following the Mets, we bring substantial writing experience to the table. Strubel, an Albany, New York native, is a freelance journalist. He is a 23-year radio host in New York, Florida, Georgia, South Carolina and North Carolina. Strubel worked in the minor league systems of the Detroit Tigers (Glens Falls Tigers) and the Tampa Bay Rays (Charleston Riverdogs). His writing has been published in magazines and newspapers in the northeast. Joura, who grew up in Staten Island, NY, has covered the NCAA Tournament, the Carolina Panthers, the Charlotte Bobcats, the South Atlantic League All-Star game and is currently a writer for RotoGraphs, FantasyPros911.com and the official scorer of the Asheboro Copperheads.
Mets360 to feature guest writers
We are proud to announce that former Mets outfielder and 10-year veteran Brian McRae will be a contributing writer to our site. McRae has already weighed in with his first piece, which gives his take on Spring Training. More guest writers will appear throughout the year, adding yet another dimension for readers of Mets360.com to enjoy.
The Stengel Awards
Our goal is to have an interactive community and therefore we have created The Stengel Awards, which will honor the most valuable performances each month. Throughout the 2010 season fans and readers can vote in a variety of categories, including "The 41 Award," "Uncle Bill," "17-karat Gold Glove" and "The Benny (Ayala) Award" for outstanding achievements.
Fresh, concise, informative, engaging and entertaining – if these are things you look for and enjoy in a Web site, then Mets360.com is for you. With content updated daily it is the latest must-see site for all Mets fans.


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Presenting Florida Bonsai to the World
Evan's Bonsai Log
A passion for trees and for learning
Welcome To My Bonsai World!
Where I create, there I am true (Rilke)
Bonsai WordPress.com site
The Wanderer's Life: Interests, connections, travels, and tales.
Just another WordPress.com site
Learning Bonsai in the Hoosier state
Being. One day at a time.
Photography On A Budget........ Grab Your Camera And Get Shooting!
A Bonsai Enthusiast's Life With His Trees
A Bonsai Apprentice Life + Times
My Life in Bonsai and Ancient trees
An American Bonsai Artist and Instructor
Perfectly Imperfect.
Design Adventures, Creative Projects and Inspirations.