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This patent application is a continuation-in-part application of U.S. patent application Ser. No. 09/134,497, entitled "VIDEO CATALOGER SYSTEM WITH SYNCHRONIZED ENCODERS", filed Aug. 14, 1998, now U.S. Pat. No. 6,360,234, which takes priority under 35 U.S.C. § 119(e) to U.S. Patent Application No. 60/055,751, entitled "VIRAGE VIDEO ENGINE", filed Aug. 14, 1997, which are hereby incorporated by reference.
The subject matter of U.S. patent applications: U.S. Patent Application No. 60/098,781, filed Sep. 1, 1998, and U.S. patent application Ser. No. 09/363,973, filed Jul. 29, 1999, and entitled "EMBEDDED METADATA ENGINES IN DIGITAL CAPTURE DEVICES"; application Ser. No. 09/134,498, filed Aug. 14, 1998, now U.S. Pat. No. 6,463,444 and entitled "VIDEO CATALOGER SYSTEM WITH EXTENSIBLITY"; application Ser. No. 09/134,499, filed Aug. 14, 1998, now U.S. Pat. No. 6,567,980 and entitled "VIDEO CATALOGER SYSTEM WITH HYPERLINKED OUTPUT"; and application Ser. No. 09/134,500, filed Aug. 14, 1998, and entitled "VIDEO CATALOGER SYSTEM WITH AUDIO TRACK EXTRACTION" have subject matter that is related to this application or was filed on the same day.
This invention was made with Government support under Contract No. DAAH01-97-C-R 190, awarded by the U.S. Army Aviation and Missile Command. The Government may have certain rights in this invention.
1. Field of the Invention
The present invention relates generally to digital capture devices, and more particularly, to digital video encoders and other media capture devices.
2. Description of the Related Technology
Today's broadcast corporations, advertising agencies, consumer products and services companies, and other businesses have demanding media asset management needs. These organizations have been simultaneously empowered by the growth in tools and infrastructure for creating, storing and transporting media-rich files and challenged by the problem of managing the media assets that they've amassed and come to rely upon for their core businesses. The sheer volume of information available over the World Wide Web and corporate networks continues to accelerate. Because media assets are so crucial to these companies, they have an extreme need for an intelligent and efficient way to catalog, browse, search and manage their media assets. Prior attempts at a content management solution have yielded point solutions or proprietary applications. These applications have not leveraged the technologies already deployed by many organizations, such as industry-standard browsers and Web servers.
A system is needed that would automatically watch, listen to and read a video stream so as to intelligently extract information, termed metadata, about the content of the video stream in real-time. This information would become the foundation of a rich, frame-accurate index that would provide immediate, non-linear access to any segment of the video. Such a logging process would result in the transformation of an opaque video tape or file, with little more than a label or file name to describe it, into a highly leveragable asset available to an entire organization via the Internet. What was once a time consuming process to find the right piece of footage would be performed instantly and effortlessly by groups of users wishing to quickly and efficiently deploy video across a range of business processes. Television and film production, Web publishing, distance learning, media asset management and corporate communications would all benefit by such technology.
The distinction between still devices and motion devices is becomming blurred as many of these devices can perform both functions, or combine audio capture with still image capture. The capture of digital content is expanding rapidly due to the proliferation of digital still cameras, digital video cameras, and digital television broadcasts. Users of this equipment generally also use digital production and authoring equipment. Storing, retrieving, and manipulating the digital content represent a significant problem in these environments. The use of various forms of metadata (data about the digital content) has emerged as a way to organize the digital content in databases and other storage means such that a specific piece of content may be easily found and used.
Digital media asset management systems (DMMSs) from several vendors are being used to perform the storage and management function in digital production environments. Examples include Cinebase, WebWare, EDS/MediaVault, Thomson Teams, and others. Each of these systems exploit metadata to allow constrained searches for specific digital content. The metadata is generated during a logging process when the digital content is entered into the DMMS. Metadata generally falls into two broad categories:
Products such as the Virage VideoLogger perform the capture and logging of both of these types of metadata. The VideoLogger interfaces with the DMMS to provide the metadata to the storage system for later use in search and retrieval operations. These types of systems can operate with digital or analog sources of audiovisual content.
Digital encoding devices convert an analog video signal into a digital representation of the video, usually encoded with a compression algorithm. The analog signal can be any of NTSC, S-Video, PAL, or analog component video (Y, B-Y, R-Y). Typical encoders support one or more of these analog standards for input. Analog signals such as these are generated by tape decks, laser disks, satellite feeds, and analog cameras.
Examples of commercial digital encoding devices on the market today include:
Digital video encoders fall into two broad categories from an architectural standpoint:
For both types of digital video encoders, what is desired is the ability to extend the computations being performed to include metadata capture.
In one aspect of the invention, there is a media cataloging and media analysis application which performs real-time, or non-real-time, indexing and distribution of video across an enterprise. A multimedia cataloger is the first application to make video-based solutions pervasive in enterprise markets by creating and publishing intelligent video via the World Wide Web. The multimedia cataloger is the logical starting point for creating or distributing significant amounts of video. The cataloger transforms video into a powerful data type that is both compelling and profitable in both Web and client-server environments. Using advanced media analysis algorithms that automatically watch, listen to and read a video stream, the multimedia cataloger intelligently extracts metadata-keyframes, time codes, textual information and an audio profile from the video in real-time. This information becomes the foundation of a rich, frame-accurate index that provides immediate, non-linear access to any segment of the video.
In parallel to the indexing process, the multimedia cataloger may also optionally control the encoding of a streamable version of the original content. Synchronized encoding and indexing allows users to intelligently navigate through the video by using the index to go directly to the exact point of interest, rather than streaming it from start to finish. This approach provides video previewing that is faster than real-time, conserves valuable network bandwidth and dramatically reduces costs associated with editing and repurposing video.
The multimedia cataloger permits accessing and distributing media for digital television, Web publishing, distance learning or media asset management initiatives using advanced methods for accessing and leveraging media assets.
The present invention is based on technologies relating to the automatic extraction of metadata descriptions of digital multimedia content such as still images and video. The present invention also incorporates audio analysis engines that are available from third parties within an extensible metadata "engine" framework. These engines perform sophisticated analysis of multimedia content and generate metadata descriptions that can be effectively used to index the content for downstream applications such as search and browse. Metadata generated may include:
A central theme of the technical approach is that it is most valuable to capture this type of metadata as far "upstream" as possible. This allows the metadata to be exploited throughout the lifecycle of the content, thereby reducing costs and improving access and utilization of the content.
The present invention is based on a sophisticated video engine to automaticaly extract as much metadata as possible from the video signal. This involves visual analysis, audio analysis, and other forms of metadata extraction that may be possible in particular situations. This video engine performs sophisticated analysis of multimedia content and generates metadata descriptions that can be effectively used to index the content for downstream applications such as search and browse.
In one embodiment, the present invention may embed this video engine directly inside a workstation, for example, such that the output is not only the digital video content, but a corresponding package of metadata which is time indexed to describe the video content. In another embodiment, the video engine is embeded inside a digital encoding device. Digital encoders are rapidly advancing in capabilities and market penetration. The digital encoder embodiment of the invention embeds video and audio engines directly inside the digital encoding equipment such that the output is not only the digital video content, but a corresponding package of metadata which is time indexed to describe the video content.
In both of these embodiments, the digital video and the metadata are output together. Promising "containers" for this combined video and metadata are the proposed MPEG-4 and MPEG-7 digital multimedia formats, which, such as FlashPix for still images, are designed and intended to embed rich metadata directly in the video format to allow indexing and non-linear access to the video. The current version of QuickTime (on which MPEG-4 is based) is also an ideal container format. While these standards are still under development (and MPEG-7 is several years away) and are not in widespread use, these mechanisms are not required for the present invention. The metadata may be packaged in any form as long as an association with the original content is maintained as the video and metadata may be transferred from the workstation into subsequent asset management and post-processing applications.
In another aspect of the present invention, there is an integrated data and real-time metadata capture system, comprising a digital capture device producing a digital representation of one or more forms of media content; a feature extraction engine integrated with the digital capture device, the feature extraction engine having a plurality of feature extractors to automatically extract metadata in real-time from the digital content simultaneously with the capture of the content; and a storage device capable of storing the media content and the metadata, wherein selected portions of the metadata are associated with selected portions of the media content.
In yet another aspect of the present invention, there is an integrated data and real-time metadata capture method, comprising receiving analog signals, converting the analog signals to a digital representation of one or more forms of media content, encoding the digital media content, automatically extracting metadata in real-time from the digital media content simultaneously with the encoding of the digital media content, and storing the encoded digital media content and the metadata, wherein selected portions of the metadata are associated with selected portions of the encoded digital media content.
FIG. 1 is a block diagram of one embodiment of a multimedia cataloger system of the present invention.
FIG. 2 is an exemplary screen display of a user interface for the multimedia cataloger system shown in FIG. 1.
FIG. 3 is a block diagram of exemplary input and peripheral components for the multimedia cataloger system shown in FIG. 1.
FIG. 4 is a block diagram of exemplary components and processes used in the cataloger and encoder portion of the multimedia cataloger system shown in FIG. 1.
FIG. 5 is an exemplary timeline of encoder start-up and synchronization for the components and processes shown in FIG. 4.
FIG. 6 is a diagram of an exemplary set of metadata types in a time-based track representation as derived by the cataloger of the multimedia cataloger system shown in FIG. 1.
FIG. 7 is a block diagram of an object model for the metadata shown in FIG. 6 along with a software process that manages the metadata.
FIG. 8 is a block diagram of the software architecture for the cataloger of the multimedia cataloger system shown in FIG. 1.
FIG. 9 is a block diagram of the elements of the extensible video engine shown in FIG. 8.
FIG. 10 is a block diagram of the audio analysis extractor shown in FIG. 9.
FIG. 11 is a flowchart of the extensible video engine initialization (start-up extensibility initialization) process shown in FIG. 8.
FIG. 12 is a flowchart of the video encoding (and metadata capture) synchronization process shown in FIG. 8.
FIG. 13 is a flowchart of the capture metadata process shown in FIG. 12.
FIG. 14 is a flowchart of the feature extraction process shown in FIG. 13.
FIG. 15 is a block diagram of the architecture of the HTML output filter shown in FIG. 9 as used in the multimedia cataloger system shown in FIG. 1.
FIG. 16 is a flowchart of a HTML output filter process corresponding to the HTML output filter architecture shown in FIG. 15.
FIG. 17 is an exemplary screen display seen as an output of the HTML output filter process of FIG. 16 while using a client browser for the multimedia cataloger system shown in FIG. 1.
FIG. 18 is a block diagram of another embodiment of a multimedia cataloger system of the present invention.
FIG. 19 is a block diagram showing a generic digital encoding system containing typical elements found in an encoding system.
FIG. 20 is a block diagram showing a specific example of combining a content-based metadata engine with a digital encoding board. The encoding board contains a general purpose digital signal processor (ASP) that can be programmed to perform one of a variety of digital compression algorithms, and can be additionally programmed to perform metadata analysis.
FIG. 21 is a block diagram showing another specific example where the compression and metadata extraction are performed by the general purpose CPU of the host workstation. The capture board performs digitization of the analog signals, and passes the raw digital content to the host CPU for further processing.
FIG. 22 is a flowchart showing a generic metadata collection process within a digital encoding device such as shown in FIGS. 19-21.
The following detailed description of the preferred embodiments presents a description of certain specific embodiments to assist in understanding the claims. However, the present invention can be embodied in a multitude of different ways as defined and covered by the claims. Reference is now made to the drawings wherein like numerals refer to like parts throughout.
The detailed description is organized into the following sections: 1. Top Level System Overview, 2. Example User Interface, 3. Cataloger Configuration Detail, 4. Logging and Encoding, 5. Example Timeline, 6. Metadata Track Representation, 7. Metadata Index Object Model, 8. Cataloger Architecture, 9. Extensible Video Engine Architecture, 10. Audio Feature Extractors, 11. Extensible Video Engine Start-up Initialization, 12. Video Encoding and Metadata Synchronization, 13. Capture Metadata, 14. Feature Extraction, 15. HTML Output Filter Architecture, 16. HTML Output Filter Process, 17. Example HTML Output, 18. Alternative System, 19. Digital Encoding System. Before describing the detailed internal engineering of the inventive system, a top level system overview will be helpful.
1. Top Level System Overview
FIG. 1 depicts a typical system 100 that incorporates a Video Cataloger 110. The Video Cataloger 110 typically operates in a networked environment which includes data communication lines 112, 122, 132, and 142. Some variants of such a system include:
FIG. 2 depicts an example user interface that is representative of the type of graphical user interface (GUI) than could be built around the Video Engine shown in FIG. 9. In FIG. 2, the Video Cataloger user interface is contained in a window 170. The main controls are exposed as menus and a tool bar 182. A panel 172 displays the live video being digitized, with play, stop, etc. controls that interact remotely with the analog source via a deck controller 240 (FIG. 3). Keyframes extracted during the capture process are displayed in a panel 176, while the corresponding close-caption text and timecodes are displayed in a panel 178. A panel 184 displays the user-defined clip annotations, created by marking in- and out-points. The columns 186 and 188 display the in- and out-time codes for the marked clip, respectively, while the remaining columns 190, 192, 194 are an example of a user defined schema of labels to describe the clip. Finally, at the bottom of the window 170 is a timeline 180 that depicts the total time of the capture session, with a highlighted section corresponding to the currently selected range of keyframes.
3. Cataloger Configuration Detail
FIG. 3 depicts a typical configuration of the Video Cataloger 110 connected to various peripheral devices that interface the Cataloger to an analog source such as the videotape deck 102, a Deck Controller 240, and a close caption decoding device 230. The deck controller 240 is typically an external device that provides protocol translation between an industry standard protocol such as V-LAN, and the native protocol of broadcast devices (such as tape decks) from Sony, Panasonic, etc. An example device is the Video Media Express from Video Media Corp. Some hardware configuration may incorporate the V-LAN controller into a card in the Cataloger workstation, for instance.
The close caption text decoder 230 can be an external box as shown, (such as EEG Enterprises Digital Recovery Decoder), or the CC-text decode functionality can be incorporated on the frame capture board inside of the Cataloger workstation. Furthermore, the video signal may be routed through the close caption text decoder 230 (as shown), or it may be split and fed directly to both the video Cataloger 110 and the decoder in parallel.
The Video Deck 102 is one example of an analog source. Several others are possible: laser disk, satellite feed, live camera feed, digital disk recorder such as a Tektronix Profile, etc. Some of these configurations would not incorporate the V-LAN control (such as a live or satellite feed).
Analog signals 232 may be fed from the Video Deck 102, through the close caption decoder 230, into the Video Cataloger 110. The analog signals correspond to video information which generally includes audio information. Decoded close caption text is passed to the Video Cataloger 110 by a data connection 234 which is typically an RS-232 cable. Deck commands pass from the Video Cataloger 110 to the Deck Controller 240, and then to the Video Deck 102 by physical data connections 236 and 242 which are typically RS-232 serial connections, but may be other signaling protocols. The time codes proceed from the video deck 102 to the video cataloger 110 via the deck controller 240. Of course, in alternate implementations, the Video Cataloger 110 may receive video information from a digital source such as a digital camcorder.
4. Logging & Encoding—Detail
FIG. 4 depicts one of a great variety of possible encoding scenarios, driven by the Video Cataloger. The Video Cataloger software 110 runs on a computer workstation 111. The "Vidsync" process 260 running on each of the encoder workstations 123, 125, 127 is responsible for responding to Start and Stop commands from the Video Cataloger 110, and affecting the start and stop of the corresponding encoding process on each workstation. The analog source 102 will typically need to be split by an audio-video switcher 252 so that the signal can be fed to each receiving workstation without degradation. FIG. 4 shows examples of Real Video encoding 124, MPEG-1 encoding 126, and MPEG-2 encoding 128. Further information on the Moving Pictures Experts Group (MPEG) encoding standards may be found at the following URL: http://drogo.cselt.stet.it/mpeg. Naturally, other encoding formats are possible. All machines are connected by a data network 250, which is typically a TCP/IP network, although other network protocols may be employed.
Some of the many variations for encoding scenarios include:
The Cataloger 110 issues commands to each of the Vidsync daemons 260 running on the encoder workstations. These daemons, or processes that are periodically spawned to carry out a specific task and then terminate, are responsible for initiating the encoding process for whatever type of encoding is going to occur. That is, intimate knowledge of the encoding is maintained in Vidsync, and the Cataloger is generic in this respect. The Vidsync daemons also are responsible for returning certain pieces of information to the Cataloger, such as the actual start time, and a digital video asset ID or name for later use.
START Command: The Cataloger 110 issues a "start encoding" command via TCP/IP to each of the encoders (Vidsyncs) in parallel. Each of the Vidsyncs 260 then communicates with whatever software and hardware encoding processes/boards are required to initiate encoding. This may also involve communicating with a video server to set up an encoding session, and may take from 1 to several seconds. Thus, each encoder process may have a different actual start time. The Vidsync daemons then return the actual start time and a digital video asset ID to the Cataloger 110. When all Vidsyncs 260 have returned, the metadata capture begins at a nominal T=0 time. Each of the actual start times is stored as a delta-time from this T=0 time. When a piece of metadata (such as a keyframe) is used to index the digital video, an absolute time from the beginning of the digital video is computed by adding the delta-time to the time-code of the metadata.
STOP Command: The Video Cataloger 110 issues a "stop encoding" command via TCP/IP to each of the encoders in parallel.
5. Example Timeline
FIG. 5 illustrates the timing associated with video encoder start-up and synchronization. Each timeline 123, 125, 127 represents a separate video encoder. The Video Cataloger 110 issues a Start Command 290. Some time after that, each encoder actually begins encoding, resulting in an "actual start time" 292. After all the encoders have started, the Video Cataloger 110 itself begins cataloging metadata, at a time nominally labeled "T=0" 294. Thus, each encoder has a start offset 'delta' time 296. This delta time is then stored with the video metadata to be used later when a video stream is requested, to insure the offset is accounted for in time code calculations.
6. Metadata Track Representation
FIG. 6 is a logical illustration of a number of metadata types in the form of the preferred time-based track representation. The keyframe track 320 consists of a set of individual keyframes 340, 342, 344, 346, 348, 350, 352 which have been intelligently extracted from the video based on visual information and scene changes by the Keyframe Extractor 512 (FIG. 9). Each keyframe is time stamped for later correlation with the digital video or a time-code on a videotape.
The close caption text (cc-text) track 322 consists of sentences of text parsed from the cc-text input by the cc-text extractor 514 (FIG. 9). Each text element spans a period of time in the video, denoted by an in-time and an out-time.
Likewise, the remaining metadata tracks (Audio Classes 324, Speech 326, Speaker ID 328, Keywords 330) are each a parcel of metadata spanning a time period, and are extracted by their corresponding feature extractor shown in FIG. 9.
The Clip Track 332 is somewhat unique in that the definition/creation of this metadata is performed by a user using the GUI to mark in- and out-times, and type in associated alphanumeric data. Each bar in the Clip Track consists of a user-defined group of metadata fields that are application specific. The bar length is timespan from intime to outtime. Clips may be overlapping. Typically, the clips all have the same schema. For instance, metadata may include: Story Title, Report, Location, Shot Date, Air Date, Keywords, Summary, and so on. Each bar shows a clip label. So for instance, the clip labeled "Logo" may make use of the Story Title data item. Lastly, a Custom Trk is shown to indicate that metadata is extensible. That is, unique metadata can be defined and added to the Video Cataloger 110 by a user. Custom metadata tracks could include information provided in collateral data to the video information. For instance, global positioning satellite (GPS) data specifying latitude and longitude of a video camera and telemetry data of a vehicle carrying a video camera are examples of such collateral data.
7. Metadata Index Object Model
FIG. 7 is an Object Model of the same logical metadata illustrated in FIG. 6. The elements of this diagram depict the software objects and processes that manage this metadata. The main object, the Metadata Track Index Manager 402, is the manager of the entire index of metadata. It is extensible in that it allows registration of individual metadata track data types, and then manages the commitment of instances of that data into the index by feature extractors. There is one global metadata structure (the Session Level metadata 404) that is not time based, and contains metadata that pertains to the entire video. Here, for example, is where the information for managing and time-synching the encoded video resides (digital video ID's and actual start time offsets). User defined annotations may also exist here. Each of the metadata tracks is a collection of data objects 406, 408, 410, 412, etc. that hold the metadata for a specific feature extractor, and are sequenced in time according to their in- and out-times.
The metadata index also provides access for outputting metadata (data read-out) used by the Output Filters.
In an object oriented programming implementation, every Track data type is derived from a "virtual base class" that provides the basic functions for insertion, deletion, read-out, etc., and defines storage for the in-time and out-time of each metadata element. Such an implementation may be coded in the C++ programming language. One exemplary reference guide is C++ Primer by Stanley Lippman, Second Edition, Addison Wesley, which is hereby incorporated by reference.
|Track Data Types
|Metadata Data
|Virtual Base
|Defines In-time and Out-time for all
|image (bitmap)
|In-time equals Out-time, i.e., keyframe is
|a point in time
|Text fragment
|Each text fragment is typically a sentence
|(but not required to be so) and spans a
|time interval
|Audio Class
|Speech, Silence, Music, Applause, Siren,
|etc . . . , each spanning a time interval
|when that classification was valid
|Text fragment
|Each text fragment spans a time interval
|Word (text)
|keyword utterance spans a short
|(e,fra 1/2ee sec) time interval
|Speaker ID
|Identifiers of individuals whose speech is
|recognized . . . each Speaker ID spans a
|time interval when that speaker was
|Clip Track
|Label Set (user
|Different Label Set schemas can be used
|defined set of
|in different applications. Each Label Set
|labels): Text,
|is applied to all clips within a Cataloging
|Enums, Dates,
|session. The Clip definition spans a time
|Numbers, etc.
|interval marked by the user. Each Label
|field value is entered manually by the
|Data type
|Typically, a custom metadata generator
|defined by
|uses a custom track data type for storing
|its metadata. It could also re-use existing
|track data types such as Text Fragment.
Table 1 is a summary of the various standard metadata tracks, detailing the data types of each, and providing descriptive notes.
8. Video Cataloger—Architecture
FIG. 8 is a global architecture illustration of the entire Video Cataloger software process 420. The main components of this software are the Media Capture Services 430, the Video Encoding and Synchronization facility 450, the Start-up Extensibility Initialization manager 470, and the core Extensible Video Engine component 440. The details of the core Extensible Video Engine 440 are provided in FIG. 9. The Video Encoding and Synchronization module 450 is responsible for communicating with the "Vidsync" daemon processes running on the video encoders, e.g., 123, 125 and 127 (FIG. 4). The Media Capture Services 430 are further described in conjunction with FIG. 9. The registration interfaces for the extensible aspects of the Extensible Video Engine 440 are explicitly shown in FIG. 8. Upon start-up of the Video Cataloger 110, registration processes are invoked for the four primary extensibility aspects of the Video Cataloger: Metadata track registration 476, Feature Extractor registration 472, Output Filter registration 478, and Event registration 472. A set of output filters 484 are installed during system start-up. These registration processes, as well as user input and output functions 550, 554, are further described in conjunction with FIG. 11 below.
9. Extensible Video Engine—Architecture
FIG. 9 depicts the main architectural elements of the extensible Video Engine 440. Incoming media is processed by the Media Capture Services 430 consisting of Timecode Capture 502, Video Capture 504, Audio Capture 506, and Text Capture 508. Digital media 509 is then made available to the Feature Extractor Framework 510 for processing. Metadata from the Feature Extractors 512, 514, 516, 518, 520, 522 is then committed to the Metadata Track Index Manager 530 in a time based track representation as shown in FIGS. 6 and 7.
During metadata capture, the user may mark video clips and annotate them. This input 552 is captured by the GUI Input Capture element 550. Event monitoring 540 and dispatch 544 also occurs during capture, driven by an Event Dictionary 542. Finally, when capture is complete, the metadata may be output in a variety of formats such as Virage Data Format (VDF) 562, HTML 564, XML 566, SMIL 568 and other 570, which are managed by the Output Filter Manager 560. A VDF API and Toolkit may be licensed from Virage of San Mateo, Calif. Furthermore, the use of the format is described in "Virage VDF Toolkit Programmer's Reference". One reference for the eXtensible Mark-up Language (XML) is the following URL: http://www.w3.org/TR/REC-xml which is a subpage for the W3C. Also, information on Synchronized Multimedia Integration Language (SMIL) may be accessed at the W3C site.
The Metadata track Index Manager 530 represents the object that manages the multiplicity of metadata tracks. When data is committed to the track index by either a feature extractor 512-522 or GUI input 550 and 552 (i.e., user marks clips and annotates them), this can trigger display updates as follows: the particular metadata track that receives the data decides if this requires a display update. If so, it sends a message to the GUI Display Update Manager 554 which marks the relevant GUI object as "dirty" and in need of a redraw. In Windows Microsoft Foundation Classes (MFC), the event model allows Windows to detect these dirty GUI objects and issue redraw messages to them directly (see FIG. 12—Get Event)
The core aspects of extensibility are:
FIG. 10 depicts the architectural components of the audio analysis feature extractors 516 in one embodiment of the Video Engine 440. As can be seen in the diagram, there are various cross-couplings between these feature extractors, which may not be precluded in the extensibility mechanisms managed by the feature extractor framework 510 (FIG. 9).
The analog audio signal 592 is captured and digitized by audio digitization device 506, which may be any standard audio digitization device, such as a Sound Blaster audio card for a PC. The digital signal is then normalized by a software component 596 to account for variability in signal amplitude (volume). The normalized digital audio signal 598 is then fed into an Audio Class Profiler 600 which classifies the signal into one of several possible categories, such as "speech", "music", "silence", "applause", etc., where each of the categories may be trainable using well understood techniques, and is stored in a Class Dictionary 602. An Audio Classification (AC) Engine 604 is a modular component that is available from multiple vendors, or may be proprietary. One skilled in the relevant technology may evaluate and utilize a specific engine depending on the application requirements.
When the Audio Class Profiler 600 detects that the class is "speech", it triggers switch 610 which then allows the normalized digital audio signal 598 to pass into additional feature extractors which are capable of processing speech. A speech transcription module 620 is designed to interface with any available Speech Recognition Engine 624 using an industry standard interface 626, such as the "Speech API", or SAPI defined by Microsoft. Typically, the Speech Recognition Engine 624 utilizes a Vocabulary Dictionary 622 to aid in the speech recognition process and improve accuracy by limiting the speech domain, although this is not required. It is a typical feature of existing speech recognition engines available on the market today. Examples include offerings from IBM, BBN, Dragon Systems, SRI, and so on.
The output of the Speech Transcription Feature Extractor 620 may then be further processed as follows: the full text 628 of the transcription process may be used directly as metadata; additionally, a Keyword Spotting Feature Extractor 640 may be employed to selectively identify keywords of interest, and produce a text output 648 limited to the keywords specified by a Domain Dictionary 642. A Domain Dictionary Engine 644 is responsible for making these selections. Again, the Domain Dictionary 644 Engine is typically a modular component that may be one of several available, interfacing with the Keyword Feature Extractor normally via a standard interface 646 such as the Domain Dictionary API, or DDAPI.
The normalized digital audio signal containing speech can also be fed into a Speaker ID Feature Extractor 630 to identify individual speakers by name. A Speaker ID Engine 634 may also be a modular component that is offered by several speech recognition vendors, and interfaces with the Speaker ID Feature Extractor 630 typically via an industry standard interface 636 such as the SVAPI. Typically, the Speaker ID Engine utilizes a Speaker Dictionary 632 to constrain the space of possible speakers, and store signatures or sample speech of individual speakers which are used during speaker identification.
11. Extensible Video Engine Start-Up Initialization—Flowchart
FIG. 11 is the process flowchart for the start-up initialization of the Video Cataloger 110 (FIG. 1). This flowchart depicts the process for registering data types, algorithms, and events which are important to the extensibility features of the Video Cataloger 110.
Upon start-up of the Video Cataloger, the extensible video engine initialization process 470 is executed by the workstation 111. Starting at a begin step 702, the process 470 moves to step 704 to install metadata tracks. This occurs first since later extensions (mainly Feature Extractors) may then utilize the track data types previously installed. Built-in Track Types are installed first at step 704, followed by installation of custom track types defined by plug-in modules at steps 706 to 710. For each track plug-in, the data representation defined by that plug-in is installed at step 708.
Next, feature extractors are installed. The built-in feature extractors are first installed at step 714, followed by feature extractors defined by plug-ins at steps 716 to 722. For each plug-in feature extractor, it is first registered at step 718 with the Feature Extraction Framework 510 (FIG. 9). At step 720, each of these plug-in feature extractors may request a metadata track type to receive its metadata.
Following the feature extractor initialization, the Output Filters are initialized. As with the other elements, the built-in Output Filters are installed first at step 724, followed by the installation of plug-in Output Features at steps 726 to 730.
Finally, Events are registered. All events are application specific (i.e., there are no built-in events), and are registered by plug-ins starting at steps 734 to 740. Each plug-in may define one or more events in the dictionary at step 736, and each event will have an associated event handler registered with it at step 738. The extensibility initialization process 470 completes at an end step 742.
12. Video Encoding/Synchro—Flowchart
FIG. 12 details an important aspect of the present invention, which is the control and synchronization of the video encoding process with the metadata capture process. This synchronization is necessary because time-code indices within the metadata elements should correspond to correct and known points within the digital video that results from the encoding process.
When video capture is initiated by the user, the video encoding process 450 starts at a begin step 762 and moves to step 764 wherein the Video Cataloger 110 (FIG. 1) first issues a Start Encoding command to each of N video encoders in parallel by spawning process threads 766 for each encoder present. A process thread or a lightweight process is well understood by computer technologists. This command/control is effected by the "Vidsync" daemon process 260 (FIG. 4) running on each encoder station. These Start commands are issued in parallel so that all the encoders begin encoding as close together in time as possible. However, their exact start times will not in general, be coincident. For this reason, the Vidsync process 260 returns the actual start times to the encoder flow control, and these times are stored by the Video Cataloger 110 with the video metadata in step 774 for later use. Next, the general process of capturing metadata occurs in step 776 until the process is stopped by the user. The details of the metadata capture process 776 are provided in FIG. 13. When capture is done, Stop Encoding commands are sent in parallel to each encoder (via Vidsync) by spawning process threads 780. It is of no consequence that the N encoders may stop encoding at slightly different times, as no metadata is associated with these time intervals.
13. Capture Metadata—Flowchart
FIG. 13 details the metadata capture process 776 which is an important activity of the Video Engine 440 of FIG. 9. The metadata capture process 776 was first introduced in FIG. 12.
The capture process 776 begins with the scheduling of a system timer event in step 804 set to go off {fraction (1/30)} of a second in the future. The control flow of the process 776 immediately proceeds to the Get Event step 806 where other system events (besides the timer event) may be processed. When an event occurs, control passes to the Event Dispatcher 808 which decides if the event is one of the two types of events: a normal GUI event, or the scheduled timer event.
For a GUI event, the event is first inspected in step 812 to determine if it is an End Capture event, in which case the capture process loop terminates. If not, processing proceeds to step 816 to handle the GUI event (such as keystroke, window resized, etc.). Some GUI events may generate metadata (if the user marked a video clip), which is determined in step 818. If metadata (a video clip) was in fact generated, that metadata is committed to the Metadata Track Index Manager 530 (FIG. 9) during step 820. This also necessitates a GUI redraw, so the affected parts of the GUI are marked for Redraw in step 822.
If the event dispatched in 808 is the timer event, this signifies that feature extraction of metadata from the video signals is to take place at a feature extraction process 810. The details of the feature extraction process 810 are provided in conjunction with FIG. 14. Once feature extraction is complete, control moves to step 804 where the next timer event is scheduled.
This flow of activity is tied to the event model of the operating system under which the software application is running. The flow that is shown is an event model that is typical of a Windows MFC-based application. Other operating system platforms, such as Unix, have event models that differ somewhat. The event model illustrates how the feature extraction process fits into an application event framework. Note that, in the depicted embodiment, the Get Event task 806 is a call out to Windows MFC, which processes Redraw Events by calling the Redraw method of the appropriate GUI elements directly (this process diagram does not "call" the Redraw methods directly). Note that it is acceptable if feature extraction takes more than {fraction (1/30)} second.
14. Feature Extraction—Flowchart
FIG. 14 details the feature extraction process 810, which is an important aspect of the present invention, relying on the innovative architecture of FIG. 9.
The feature extraction process 810 begins at a start step 842 and proceeds to step 844 where the current time code is obtained by module 502 of FIG. 9. This time code is used by all feature extractors to time-stamp the metadata they extract. Next, all digital media is captured in step 846 by modules 504, 506, and 508 of FIG. 9. This digital media is then passed on to the Feature Extractor Framework 510 (FIG. 9) for processing. The Feature Extractor Framework 510 spawns a process thread 850 for each feature extractor. Each feature extractor processes the digital media in step 852 in whatever way it desires, for example, extract a keyframe, classify the audio signal, etc. In certain cases, but not all, some metadata will be generated from this process. Step 854 determines if this is the case, and if so, the metadata is passed to the Metadata Track Index Manager 530 (FIG. 9) during step 856. Since metadata is usually displayed in real-time in the GUI, the GUI is marked for redraw in step 858. One particular exemplary feature: extractor for video keyframes is described in the pending U.S. patent application entitled "Key Frame Selection" filed on Jun. 6, 1997.
When all feature extractor threads complete, as determined at wait (synchronization) step 862, control is returned to the capture metadata process at end step 864.
15. HTML Output Filter—Architecture
The Output Filter Manager 560 (FIG. 8) may utilize a HTML output filter 564 in one embodiment. Referring to FIG. 15, elements of FIGS. 1, 2 and 9 are shown together as utilized in generating HTML output. The user may invoke a GUI command such as the "Save-As" command on the "File" menu 553, which in turn provides a list of output filter choices (HTML, Real Networks SMIL, XML, custom, etc.). When the HTML filter 564 is invoked, it accesses the metadata in the Metadata Track Index Manager 530 and processes it into HTML form in a browser window 916 (FIG. 17), which also involves keyframe images in a keyframe frame 176 (FIG. 2) or 904 (FIG. 17), and the digital video 142 (FIG. 1) or as seen in a video frame 896 (FIG. 17). For instance, hyperlinks may be formed from displayed keyframes to video sequences. The digital video 142 may or may not be served by a content server 140. For instance, it could be a simple file on the file system of the client computer or, say, a networked mass storage device visible to the computer.
Some key features of the Video Cataloger HTML output are:
FIG. 16 details a HTML export process 890 from the Video Cataloger. This process 890 is performed by module 564 identified in FIGS. 9 and 15.
The output process 890 starts at a begin step 892 and proceeds to step 894 to process the session level metadata. This metadata is not time-based, but rather is descriptive of the entire logging session. The session level metadata corresponds to the information 404 generated by the Metadata Track Index Manager 402 shown in FIG. 7. The nature of the session level metadata is a schema which may be defined by the user, in addition to standard items such as the location where the video is taken. This information is encapsulated in an HTML frame 896 used to view this data on request, and is linked to the main HTML frame 916.
The next step is to process the keyframe track in step 898. Keyframe images, which are captured raster images, may be converted to JPEG images suitable for display in a web browser. JPEG is but one possible viewable format. For convenience, the JPEG image files 900 may be stored in a separate subdirectory of the Cataloger file system. At step 902, the keyframe track is then further processed by constructing an HTML keyframe frame containing the keyframe time code information used to invoke video playback in 896, and establishes hyperlinks directly to the corresponding JPEG images 900.
Next, the close caption text track is processed in step 906. The cc-text is output into an HTML frame, with hyperlinks created from time-codes into the keyframes of the HTML keyframe frame 904. This allows the user to click on cc-text elements, and invoke the corresponding set of related keyframes.
Video Clips are processed in step 910. The clips (defined by in- and out-times, and a user defined set of text labels) are output into an HTML Clip frame 912. The time codes are used to establish hyperlinks into the corresponding close caption text 908, and the corresponding keyframes in keyframe frame 904.
Finally, a main HTML page that incorporates the above frames is constructed in step 914. This HTML page embeds all the other frames for display and navigation. A video play-out helper application to decode and display video can be embedded in the web page frame. Examples of helper applications include RealPlayer (for RealVideo), Compcore SoftPEG (for MPEG) and Apple Quicktime.
Exemplary reference guides which could be useful to write the code to automatically generate HTML are HTML: The Definitive Guide, The second Edition (1997) Chuck Musciano and Bill Kennedy, O'Reilly & Associates, Inc. and "Treat Yourself Web Publishing with HTML", Laura LeMay, Sams Publishing, 1995, which are hereby incorporated by reference.
Note that this process flow is one example which incorporates a subset of all available metadata tracks. The output process 890 described above generated the exemplary screen shot in FIG. 17.
17. Example HTML Output—Screen Shot
Referring to FIGS. 16 and 17, a screen shot of the HTML output as seen at a client browser and as generated by the HTML output process 890 (FIG. 16) will be described. Element 896 corresponds to the video frame in the upper left portion of the screen display. Element 904 corresponds to the keyframe frame in the lower left portion of the screen display. Element 908 corresponds to the cc-text frame in the lower right portion of the screen display. Element 912 corresponds to the clip frame in the upper right portion of the screen display. Element 916 corresponds to the whole browser window. As with most browsers, including Microsoft Explorer and Netscape Navigator, if the displayable page is larger than the physical display, the browser will cause the page to be scrolled. Video data is retrieved by sending a time code to the embedded player application. The player application then retrieves the video, seeks to the requested time code (in-time), and begins playback. The user can interrupt the playback using standard VCR type controls on the player.
The HTML code for an exemplary screen display is provided in the Appendix of U.S. patent Ser. No. 09/134,497, which has been previously incorporated by reference. Sheet A of the Appendix list the directory names (clip and icons) and file names at a top level. Sheet B lists the files in the clip directory, while sheets C, D and E list the files in the icons directory. Sheet F lists the HTML code for the top level index.html file which provides the framework for the display shown in the browser window 916 (FIG. 17). Sheet G lists the contents of the topr.html file (as would be seen in the clip frame 912 (FIG. 17)). Sheet H lists the contents of the video_label.html file. Sheet I lists the contents of the video_mbase.html file. Sheet J lists the contents of the video_netshow.html file. Sheet K lists the contents of the video_noproxy.html file. Sheet L lists the contents of the video_ovs.html file. Sheet M lists the contents of the video_real.html files. Sheets J, K, L, and M may be used to provide the proxy video to allow different video formats to be displayed in the video frame 896 (FIG. 17). Sheet N lists the contents, including a set of keyframes and corresponding timecodes (as would be seen in the keyframe frame 904 FIG. 17)), of the 0001.html file in the clips directory. Sheet P lists the contents, including a set of icons in a closed-caption text frame (as would be seen in the cc-text frame 908 FIG. 17)), of the 000r.htrml file in the clips directory. The remaining sheets in the Appendix are alternate instances of the contents shown in exemplary sheets N and P. Of course, other programming languages besides HTML code could be used to implement hyperlinked output conversion.
18. Alternative System
An alternate embodiment 940 of the video encoding process, which involves a video server 942, is shown in FIG. 18. In this scenario, digital video is encoded in a MPEG stream on the Cataloger workstation 111. The data stream is broadcast as a set of UDPs (Universal Datagran Packets) 946 on a specific port number (configurable). UDPs is a standard which is a member of the IP family of protocols. When cataloging begins, the Video Cataloger 110 sends a START command 944 to a Vidsync process 260 which is running on the content server 140 where the video server software process 942 is running. Vidsync 260 in turn tells the video server 942 to "start listening" for UDP packets 946 on the specific port number. The video server 942 then begins "catching" the UDP packets 946, and converting the MPEG data into a digital video asset on that server 942. As always, metadata 112 is sent from the Video Cataloger 110 to the metadata server 130 in parallel to this encoding process. When a STOP command 944′ is issued, Vidsync 260 signals the video server 942 to stop listening for the UDP packets 946.
19. Digital Encoding System
FIG. 19 is a block diagram that shows the overall system architecture of a digital encoding system 1100. The digital capture system 1100 comprises a visual and audio capture subsystem 1200, a content-base metadata generation engine 1300, a data formatting unit 1500 with time code marking 1600, and data output and/or storage 1700.
The visual and audio capture subsystem 1200 is well known by designers of digital video encoders. The subsystem 1200 may consist of an analog video input module 1201 (such as for NTSC, PAL, SECAM, S-video, and component video streams, etc.) and an audio input module 1202, if audio is being captured. The analog signal is converted to digital form and may be filtered by analog-to-digital units 1203, 1204. The digital content is then stored in memory units 1205, 1206, such as a frame buffer for an image or video frame. The digital content may then optionally be compressed at blocks 1207, 1208 prior to being formatted at unit 1500 for output or storage 1700. In one embodiment, the video frames are time coded with information from the time code generator 1600. In another embodiment, the time code is applied and associated with the digital content representation at memory units 1205, 1206.
A content-based analysis engine 1300 accesses the digital representation of the content from the memory units 1205, 1206 to perform metadata extraction, such as keyframing, speech analysis, and so on. Since the digital content is time based (e.g., audio/video), then the metadata is time coded with timing information from the time code generator 1600. This ensures that the metadata is synchronized with the digital content it describes.
The formatted output of the formatting unit 1500 may be handled by the output system 1700 in a variety of ways. The metadata may be combined with the actual digital content in certain formatting scenarios. Combined formatting ensures the metadata is always associated with the content as the content moves through its production and archive life cycle. Examples of combined formats that exist today or are emerging in the standards bodies include Apple QuickTime (and the related MPEG-4 standard), and MPEG-7. Each of these formats contains data structures for placing arbitrary metadata along side the digital content. Further, the output system 700 may take various physical forms, such as a digital tape (examples include D1, D3, D5, DVC, Digital Beta, etc.), a local hard disk using a file-system approach, or a network based approach where the digital bitstream is transmitted to a networked storage system, such as a video server. If the metadata is not combined with the digital content, the metadata may require a separate storage or digital interface mechanism.
FIG. 20 is a block diagram that shows a specific example of the digital encoding system 1100 containing an embedded content-based analysis engine 1301. This example may be embodied as an encoding board subsystem placed in a standard computer workstation. Encoding boards such as this may contain a mixture of dedicated hardware for digitization and processing with a general purpose digital signal processor (DSP), such as a TMS320CXX series DSP available from Texas Instruments, which runs microcode to perform the compression processes at blocks 1207 and 1208. Examples of this type of encoding boar the Osprey-1000, (which can be programmed to encode into H.263, H.320, RealVideo, and other analog streams), and the Optibase MovieMaker which encodes into MPEG 1. The Osprey-1000 board utilizes a programmable DSP, referred to as a VCP, available from vendor 8×8. The VCP may be used as a specialized audio/video chip to extract keyframes while encoding RealVideo, for example. The DSP may be additionally programmed to perform the functions of the metadata analysis engine 1301.
Analog video and audio is digitized by a video analog-to-digital (A/D) converter 1203 and an audio A/D converter 1204, respectively, and the digital signals are stored in the frame buffer 1205 and the sound buffer 1206, respectively. The image frame may be stored as an RGB frame buffer 1205. Audio information may be digitized as a sequence of 8-bit or 16-bit waveform samples at a suitable sampling frequency, such as 44.1 kHz (for CD quality audio). Both the video frames and the audio signal may be compressed by the video compressor block 1207 and the audio compressor block 1208, respectively, to reduce storage requirements. There are many compression schemes currently practiced in the industry, such as simple intra-frame compression (e.g., MotionJPEG) to more advanced inter-frame compression schemes (e.g., DV and MPEG), which also include data tracks for compressed audio.
The frame buffer 1205 and sound buffer 1206 are accessed by the audio/video analysis engine 1301 which performs metadata extraction. In one embodiment, the audio and video engines offered as suitable examples for function 1301 are described above in conjunction with FIGS. 8, 9, 10 and 14.
Content-based metadata from the analysis engine 1301 is sent to a formatting unit 1503, where time codes from the time code generator 1600 are applied to synchronize the metadata with the video content. Output from the formatter 1503 is, in one embodiment, in the form of an MPEG-7 stream, which functions as a data container that packages the compressed audio/video stream with the metadata. The MPEG-7 stream is then passed to a local storage unit 1702, which may be a hard disk or other mass storage device within the computer workstation.
FIG. 21 is a block diagram that shows another example of the digital encoding system 1100 containing the embedded content-based analysis engine 1301 for metadata capture. The block of FIG. 21 is similar to FIG. 20, except that the compression (blocks 1207 and 1208) and metadata extraction computations (engine 1301) are performed in software on the general purpose CPU of the computer workstation. This architecture is exemplified by Real Networks software version of the RealVideo encoder, and the Microsoft NetShow encoder. The digital capture board may be any of a wide variety of boards supported by the station operating system. For Windows, this may include the Osprey-100, boards from Sigma Designs, Matrox, Diamond Video, and so on.
FIG. 22 is a flowchart that shows a metadata collection process 1800 that occurs inside the digital encoding device such as a programmable digital capture board. The main loop of this process checks the sources of metadata and gathers any available metadata. The main loop then time-stamps the metadata and sends it to the formatter, 1500. This loop (states 1804 to 1842) processes rapidly, such as 10 to 30 times per second so as to analyze and capture the metadata in real-time.
At the top of the loop, the first check is to see if the device is in an encoding function at a decision state 1804. If it is encoding, then the flow of control passes to function 1806 for the content-based signal analysis to take place. This function may be performed, for example, by the media analysis portion of the Extensible Video Engine described above in conjunction with FIGS. 8, 9, 13 and 14. Alternatively, it may be a more limited metadata extraction process, such as performing speech-to-text transcription or keyword spotting. An example of such a module is the Virage Audio Engine, whose architecture is described above in conjunction with FIGS. 9, 10 and 14. Any metadata generated by this function 1806 is added to a metadata batch under construction.
Once all the metadata is gathered for the current pass, it is composed into a data structure by function 1838. Then the metadata batch is time-stamped at function 1840 by obtaining the current device time code value from the timecode generator 1600. In one embodiment, SMPTE time code is used, in the form HH:MM:SS:FF (where FF is the frame count). Finally, the complete metadata package is sent at state 1842 to the format unit 1500 for preparation for storage.
In point of fact, the allocations of support hardware, computer workstations and software processes are only described here as but one example. Many other functional partitions can be defined to implement the present invention.
While the above detailed description has shown, described, and pointed out the fundamental novel features of the invention as applied to various embodiments, it will be understood that various omissions and substitutions and changes in the form and details of the system illustrated may be made by those skilled in the art, without departing from the concepts of the invention.


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Researchers created a "superlattice" of two graphene sheets stacked together — not precisely on top of each other, but rotated ever so slightly, at a "magic angle" of 1.1 degrees. The hexagonal honeycomb pattern is offset slightly, creating a precise moiré configuration that is predicted to induce strange, "strongly correlated interactions" between the electrons in the graphene sheets. In any other stacked configuration, graphene prefers to remain distinct, interacting very little, electronically or otherwise, with its neighboring layers.
The team, led by Pablo Jarillo-Herrero, an associate professor of physics at MIT, found that when rotated at the magic angle, the two sheets of graphene exhibit nonconducting behavior, similar to an exotic class of materials known as Mott insulators. When the researchers then applied voltage, adding small amounts of electrons to the graphene superlattice, they found that, at a certain level, the electrons broke out of the initial insulating state and flowed without resistance, as if through a superconductor.
"We can now use graphene as a new platform for investigating unconventional superconductivity," Jarillo-Herrero says. "One can also imagine making a superconducting transistor out of graphene, which you can switch on and off, from superconducting to insulating. That opens many possibilities for quantum devices."
The behavior of strongly correlated materials, and in particular unconventional superconductors, has puzzled physicists for decades. Such difficulties have stimulated new research paradigms, such as ultracold atom lattices for simulating quantum materials. Here we report on the realization of intrinsic unconventional superconductivity in a two-dimensional superlattice created by stacking two graphene sheets with a small twist angle. For angles near 1.1°, the first 'magic' angle, twisted bilayer graphene exhibits ultraflat bands near charge neutrality, which lead to correlated insulating states at half-filling. Upon electrostatic doping away from these correlated insulating states, we observe tunable zero-resistance states with a critical temperature Tc up to 1.7 kelvin. The temperature–density phase diagram shows similarities with that of the cuprates, including superconducting domes. Moreover, quantum oscillations indicate small Fermi surfaces near the correlated insulating phase, in analogy with underdoped cuprates. Its relatively high Tc, given such a small Fermi surface (corresponding to a record-low two-dimensional carrier density of about 1011 per square centimetre), puts twisted bilayer graphene among the strongest coupling superconductors, in a regime close to the crossover between the Bardeen–Cooper–Schrieffer regime and a Bose–Einstein condensate (BCS–BEC). These results establish twisted bilayer graphene as the first purely carbon-based two-dimensional superconductor, providing a highly tunable platform with which to investigate strongly correlated phenomena, which could lead to insights into the physics of high-Tc superconductors and quantum spin liquids.
Nature – Unconventional superconductivity in magic-angle graphene superlattices

subset: commoncrawl


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Qween City is thrilled to be highlighting the city & region's myriad artisan makers this holiday season. If you would like to be highlighted in the Craftiste directory, please shoot an email to firstname.lastname@example.com.
How long have you been an artisan & business owner in Buffalo?
I have been in business for about 6 years now 🙂
Where are you located in the city / region?
I am actually outside the city in the MIDDLE of no where ( Forestville NY)
Do you have a physical storefront? If so, what is the address?
I am actually in the process of opening one 😉 Stay tuned
Have you operated elsewhere?
No 🙂 Buffalo Born and Raised
Please describe your work / product; if applicable, please include your artist / personal statement or mission.
Rusterior is an Eco friendly hand pressed print shop of clothing and home goods. We focus on quality products that are printed by hand in our studio right outside of Buffalo NY. The printing is simple, eco friendly, and unique. We also strive for a sense of community in everything we do from our business practice to our wears. We hope to bring the community together so we can all empower each other and succeed!
Who are some of your favorite artisans / makers in the region?
There are so many! Honestly I love every Buffalo Boss Babe in WNY it is such an amazing community to be a part of – My Small Business bestie is Christy from Wild Blossom Hollow 🙂
Where will you be representing your wares this holiday season?
We are currently in Fern+ Arrow on Elmwood, Beulah's General Store in East Aurora, Fredonia Farmhouse Finds, Bay 6 Clothing Company as well as nationally stocked. You can also find us at many artisan markets. The few we have left include Pop UP and Jingle at Resurgence, WNYBAC Last Minute Panic and the Muse Jar holiday show.
If there's anything else you'd like to include, please feel free to do so below!
On top of my company I am also the founder of Buffalo Boss Babes a blog featuring amazing woman in and around buffalo doing amazing things follow along to learn more about the movers and shakers <3 Buffalobossbabes.com


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Introducing... our new weather presenter Holly Green
Holly is a Met Office trained forecaster with an MSc in Meteorology.
After completing her studies at Reading University she spent a year training as a forecaster before heading to RAF Coningsby.
Whilst there she provided detailed forecasts and daily briefings for the aircrew of the Eurofighter Typhoons and classic World War II aircraft of the Battle of Britain Memorial Flight. (You have to be pretty sure of your forecasting skills to tell a room full of pilots they can't go flying!)
Holly was then offered a job with BBC Weather where she briefed the national and regional presenters before eventually making her own move in front of the camera.
Now she is delighted to be joining the Meridian team where she can use her experience to keep the region up to date with the forecast every day.
Welcome Holly!


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About Us
NWSPR Mission Statement
Collectively we exemplify professionalism in the industry of physician recruitment, earning the respect of healthcare providers, administrators and the community by improving population health through expert recruitment.
We provide a venue for members of Northwest Staff Physician Recruiters to collaborate by sharing knowledge, experience, and information promoting the success and professional development of each member. Through educational programs, shared resources, and collective expertise, we share best practices for the achievement of high performing recruitment, on-boarding, and retention.
Northwest Staff Physician Recruiters
409 Maynard Ave S Ste 109
Seattle, WA 98114
President Jana Mastandrea FASPR, Providence Health & Services Address:Seattle, WA Work: 425-525-5854 firstname.lastname@example.com
Jana Mastandrea has been a Physician Recruiter for 11 years. Jana started her career as a Physician Recruiter working at a large academic institution in upstate NY, Albany Medical Center, in 2007.During her time at Albany Medical Center she was responsible for provider recruitment, provider- onboarding, and contracting. She later transitioned into a physician recruitment manager position in 2014 with Ellis Medical Center which is another large hospital system in upstate NY. During her time as a physician recruiter in NY she was a member of ASPR, Upstate NY Physician Recruiters, Academic In house Recruiters (AIR), Onboarding and Retention (OAR), and The North East Physician Recruiters Chapter. Jana moved to Seattle in 2016 and is now a member of the NWSPR chapter. She has been working for Providence Health as a senior physician recruiter since May 2016. Jana has a bachelor degree in Business Administration that she earned at Empire State College in NY. Jana has also completed all of the ASPR fellowship exams and has her FASPR designation.
Vice President Allyson Hollingsworth FASPR, Provider Solutions + Development Address:Seattle, WA Work: 425-525-5994 firstname.lastname@example.com
Allyson Hollingsworth, FASPR, is the Provider Recruiter for Provider Solutions + Development. This position allows her to be a resource for Montana hospitals and clinics looking to fill employment opportunities, as well as for candidates looking to work in Montana. Allyson originally grew up in Tukwila, Washington and moved to Montana to attend Carroll College. She graduated from Carroll College in May of 2016 with a dual Bachelor's in Public Health and Health Sciences. Allyson is now pursuing a Master's degree in Healthcare Administration from Colorado State University-Global Campus. She became a Fellow of ASPR in July of 2017. She has a demonstrated history of working in the hospital & health care industry, including in clinics, nursing homes, and the hospital association. In her free time, she enjoys cooking, the outdoors, attending concerts, and photography.
Secretary Lori Stephenson CMSR, Astria Regional Medical Center Address:Yakima, WA Work: 509-575-5183 email@example.com
Lori Stephenson is currently the Director Integrated Marketing and Physician Relations at Astria Regional Medical Center. She has been a member of ASPR since 2006 and has completed the CMSR certification through the American Academy of Medical Management.
Treasurer Kris Collins FASPR, Providence Health & Services Address:Seattle, WA 98107 Work: 425-525-5854 email@example.com
I have been recruiting for 10+ years in a variety of industries from light industrial staffing to public health navigators setting up Covered California entities for the Affordable Care Act and dairy machine managers for the largest cheese manufacturing plant in the US. None of that compares to the complexities I encountered in physician recruiting when joining Providence. I owe much of what I've learned of the foundations of physician recruitment to ASPR, and I'm so grateful for the community of recruiters in NWSPR and would be honored to serve as secretary on the board".


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The Music Mix has learned that Bruce Springsteen and the E Street Band will perform as planned at the first of two Rock and Roll Hall of Fame 25th Anniversary concerts in NYC this Thursday.
The band cancelled its Kansas City tour stop last night on short notice due to a death in the family. Later reports explained that Lenny Sullivan, Springsteen's cousin and an assistant road manager for the band, had died unexpectedly at age 34 before the show. News of this sad loss traveled quickly through the Springsteen fan community; we at the Music Mix join in sending our most heartfelt condolences to the Boss.
Many wondered last night whether or not the band would play their next scheduled date, the Hall of Fame show. A spokesperson for the concerts tells the Music Mix that Springsteen and the E Street Band are, indeed, still set to perform. Surely no one would have blamed them if they'd wanted to take another night off, but it's good to know they're able to go on in the face of tragedy.
Were you planning to attend the Kansas City show, or will you be there at the Hall of Fame performance? Share your thoughts below.
(Follow the Music Mix on Twitter: @EWMusicMix.)
More from EW's Music Mix:
Bruce Springsteen on the Music Mix
Norah Jones' "Chasing Pirates" video
Leonard Cohen at Madison Square Garden: The master at 75
'Once' more: The Swell Season's Glen Hansard and Marketa Irglova
Photo credit: Brian Hineline/Retna


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Fresh Fire for all Nations reaches out to the poor through Mercy Relief Mission a charity arm for the ministry.
In 2004 the ministry was granted 12 hectors of land by the Zambian Government for the purpose of the Humanitarian works.
That same year, one family orphanage house was built in partnership with the Japanese Christian orphanage
organisation. There is still need to further develop the land.
One of the greatest World's enemy and the today's number one problem is poverty. It's a
fight that we should not give up, a fight that has to be won! We can not completely
eradicate poverty on the face of the earth, however it can be alleviated, reduced as we join
hands to help the needy – and save millions of lives
who are starving in some parts of the of World – Martin Njamba.


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You are here
New Trier grad Cook makes drastic career change post-basketball5:00 am CDT August 13, 2019 Sports, Alumni-College
The way Steven Cook saw things, playing basketball overseas was an experience. After a stellar season at Princeton, he'd put in his time, see the world, make some friends.
And he did that from 2017 to 2018, playing for...
Loyola grad Wieczorek and Pepperdine teammate Michael Wexter to play together in Germany5:00 am CDT August 7, 2019 Sports, Alumni-College
Michael Wexter and David Wieczorek have come a long way in five years.
The pair, who were members of the Pepperdine University men's volleyball team, are both Chicago-area natives. After playing together for the past...
Alumni Spotlight: New-found confidence helps Harvard's Boehm change mindset5:00 am CDT July 31, 2019 Sports, Alumni-College
She started every game growing up and 68 games at Harvard, then Jeannie Boehm was benched.
Harvard head coach, Kathy Delaney-Smith, made the bold decision. She was impatient with Boehm. She wanted Boehm to be more...


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If you are suffering from calf muscle soreness or cramps in your calves during long runs, brick sessions or during races, the solution may be as easy as drinking more water before and during the run.
Removing the fact that there may also be other issues causing this problem such as a weak core, poor running technique, incorrect shoes, etc. However the main focus of this article will be water intake.
One day I found myself discussing some problems I was having with my massage therapist. I explained to her that I thought I was on the edge on getting injured. The problem I was having was that I found myself walking home after 90 minutes of running due to my calves feeling like they were on fire. She instantly asked how much water I was drinking before and during the run and advised me to increase my water intake.
I took her advice on board and as soon as I started to drink more, the problem disappeared.
A friend of mine was complaining to me that he kept on getting cramps in his calves during races. He explained to me that he had seen physiotherapist, nutritionist, podiatrist to help fix the problem and no one was able to help. As soon as I asked about the amount of water he was consuming during the bike, something instantly clicked. His next race, he won his age group without any cramping problems.
If you do find you still struggle with these problems, really look closely at the amount of water you are consuming. Be careful not to go overboard with the fluids, as always, test in training during your long runs and race simulation brick sessions.
Tim Egge


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I am a full-time freelance Graphic Designer living in Madison, Wi. I have a Marketing and Graphic Communications degree with 6+ years of design experience. I got my roots in the Casino business designing marketing and in house print material for casino promotions and events. Working in the corporate environment and living in a cubicle can only go so far with a creative mind like mine, so I decided it was time to take it to the road and freelance full time. Since then some of my clients have included everything from small start up companies, non profits, politicians, national organizations, major casinos to a friend who wants to customize their bicycle with some sweet stickers.
When I'm not designing you will most likely find me on my bike. I am a professional mountain biker which allows me to see the country on 2 wheels and gives my creative inspiration the edge over anyone else. While riding, your mind is clear and allows you to think with out all of the everyday commotion. You can follow my progress through the design process and see me push my body to the limits on the bike at my blog.
Think I'd be a good fit for your next project? I'd love to work with you. Get in touch by filling out the form on my contact page.


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new old kid on the blog, with an occasional old or new poem written off the old writer's block
Saturday, November 26, 2011
Surreal Sleepwalker
5 comments:
That half awake asleep state can seem surreal. This is lovely Vassilis, that moon waxing the blue ocean floor at your feet.ReplyDelete
However do you find such words and put them together to create whole new worlds of sensation?
Now what's what I call a proper shoeshine, you old surrealistic sleepwalker, you.ReplyDelete
Blue and moon
divine in time
No better rhyme
than shoe
However do I find such words? I'm a good sleep writer? =:)! Seriously, I don't know the answer but I'm going to sleep on it! Thanks for responding.
Perhaps this is a key to answering the question that Elisabeth has: My old shoeshine box! In the meantime, I thank you, my good sir and spit on your shoes, to boot!
- AnonymousNovember 28, 2011 at 5:15 AM
Perfect! I've been moon-watching myself, but nowhere near the ocean. Now I feel I've seen it....ReplyDelete
Glad I could help and good to hear you liked it.


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What are your favorite makeup colors to wear during Spring?
Shop My Look- actual and similar products to the one's I used (affiliate links):
I'm a brown eyed girl too, and I also love lavender/purple shades for the eyes. I love seeing your makeup tips and you're so cute too! I've never tried Urban Decay products but I keep hearing how good they are. I may have to give them a try. :)
You gorgeous woman! Love how this look is sultry without being heavy. Beautiful!
You're so sweet, Lisa..thank you!!
That's so cool that we share the same love of purple!! I think you will love Urban Decay..their eyeshadows are extremely pigmented!
Thanks, Amy!! I used to really pile it on the eyes but have started to lighten things up a bit :)
Pretty. Love your smudge technique for liner. Pinned
Thanks Michele!!
Selene, your eyes look beautiful! I LOVE the pink shadow you used and I am not really a pink person. I might have to try some pink shadows now, thanks for sharing :)
Thank you, Meg! You are so sweet :)
I love the look! It's so pretty and soft!
Well aren't you just the cutest, and the makeup is to die for!
Jessica, you are too sweet! Thanks!
I've always LOVED purples!! Thanks for stopping by :)
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Larry, Computer Controlled, DJ AcidTed, DJ Frantik. So many names, not enough Acid! Born in the Midwest, the birthplace of Acid House music no less...
Cubensis, a native of Fond du lac, WI, has lived all over North America and music has followed him wherever he goes. Starting early as a drummer and...
Dakota Veer aka Cody V, has certainly broken some major ground over the past few years. With 10+ releases on beatport via woody mcbrides Communique...
Doug AKA DJ Klypz, commonly known as the man with the big... soundsystem. Has played a pivotal role in CI. Being the main sound/light man for almost...
Mike AKA Poohbear AKA DJ Relic. An old school champ, professional chef, father of 2, and the best friend anyone could ever hope to have. Mike...
haloscope -
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Representing the city of Waupun, WI, Martin.Joseph is "one of the best damn djs i have ever seen". PERIOD. Bringing all that is house into his sets...
Growing up on "the edge of the world" Laredo, TX. Mark has "been there" and back. What hes brought back with him is something you need to hear. A man...
T.Rux, aka Ted Mueller aka ME. I can type for days about everyone else, but I dont know what to say about myself. I started DJing when I was about...
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Here are all the weird side projects, webcasts, spots, and live recordings from the past few years of Collective Intelligence!
DJ Relic
Electronic - Trance
Mike AKA Poohbear AKA DJ Relic. An old school champ, professional chef, father of 2, and the best friend anyone could ever hope to have. Mike currently resides in Door County Wisconsin (the part of wisco that looks like a huge cock, which coincidentally... no I wont go there)
Well it took awhile to get poohs profile up here, and it might take a bit longer to get some mixes up. but, check for him comin to a dancefloor or kitchen near you soon!
Contact Mike
Currently Residing in Door County, WI
For Booking infoClick Here
Debut EP with work feauting MykeMyth
Created in a late night session, madison, wi january 2011
Song Length6:00
GenresElectronic - House, Electronic - Trance
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When you are looking for the perfect way to clean your garage, workspace, or workshop, it seems like the cleaning process is never totally finished. With the constant movement of tools, supplies, etc. it seems like there is always debris and dust lying around somewhere that you missed, even if you just cleaned it.
The difference between having a clean shop and the cleanest shop is all in the shop vac that you are using to clean up. Today, we are going to look at some of the top performing shop vacs on the market, and give you a breakdown of the features, pros, and cons of each.
The Best Shop Vac For Dust Collection Comparison
WORKSHOP Wet Dry Vac WS1600VA
Craftsman XSP 12 Gallon
Dustless Technologies
Shopvac 5950800
Vacmaster 5 Gallon
Best Shop Vac For Dust Collection Reviews
1. WORKSHOP Wet Dry Vac WS1600VA
Editor Rating:
If you are looking for a reliable, large, vacuum that comes with a lot of great attachments and features, you are going to really like the Workshop WS1600VA. It comes with a 2 ½ inch diameter and 7 foot hose that is perfect for sucking up dust and debris around your shop. The hose locks perfectly onto the vacuum and all of the attachments so that you don't have to worry about it falling off or sliding off.
What we love about the hose is that it isn't stiff like some hoses. It offers 180 degree flexibility to it is great for getting tight corners, and anywhere that you can imagine. The vacuum has on site storage for your attachments so that they are always within arms reach. It also includes a blowing port that you can use to blow your shop clean.
What We Liked
What We Didn't Like
2. Craftsman XSP 12 Gallon Wet/Dry Vac
Editor Rating:
This Craftsman vacuum is another large shop vacuum with a 12 gallon tank, and it is great for sucking up dust, debris that is large or small, wet or dry. It comes with a few different attachment heads for a variety of different surfaces and circumstances. This vacuum provides about 120 volts of power and weighs in at almost 25 pounds, so you know that it is sturdy and durable.
We also really like that this vacuum comes with a one year warranty from Craftsman, so if you have any issues with it, you can get assistance from the manufacturer.
What We Liked
What We Didn't Like
3. Dustless Technologies 16003 Wet/Dry Vacuum
Editor Rating:
The Dustless Technologies 16003 vacuum is an impressive model that remedies the mess that some vacuums can create. In terms of clean up, most vacuums will get the job done. The only troublesome part is after you are done vacuuming, and their is a mess of dust and debris inside of the vacuum that you need to dispose of. This model from Dustless is super easy to clean, after you are done using it.
It is able to switch from wet to dry vacuuming work without having to switch between dry and wet filters, which is a nice touch. This vacuum works great on concrete floors, and has no problem cleaning up drywall debris and dust. The filters that it uses are reusable and washable, which is another nice touch. This vacuum is specifically designed to clean up seriously small dust particles without a problem, and without the mess of your traditional shop vacuum.
What We Liked
What We Didn't Like
4. Shopvac 5950800 Wet/Dry Vacuum
Editor Rating:
This Shopvac model is another reliable vacuum for picking up dust and small debris in your workshop or garage. This vacuum is actually a little smaller than some of the other vacuums that we have looked at, but can still hold 8 gallons of dust and debris. This vacuum comes with an eight food hose that locks on to the base of your vacuum so that you don't have to worry about it coming loose, while vacuuming.
It also has a six foot long power cord, which is a great start for reaching across your workspace. This vac includes carry handles on the sides and the top, so that it is easy to carry around and transport. It also has a filter minder that helps you maintain your filter so that you don't wreck it. Comes with a 10 inch nozzle that is great for both wet and dry cleanup. It also comes with a crevice gulper nozzle, collection bag filter, and cartridge filter.
What We Liked
What We Didn't Like
5. Vacmaster VJC507P 5 Gallon Wet/Dry Vacuum
Editor Rating:
The Vacmaster 5 gallon vacuum is by far the smallest and most compact vacuum that we are going to take a look at today. That being said, this would be ideal for smaller workshops, garages, etc. and is going to be really easy to store in a small place. It comes with a six foot hose and an eight foot cord, with a wrap for the cord. It also comes with a three piece extension wand, and a noise diffuser to muffle the noise of the vacuum. This vacuum also includes a reusable cloth filter and a reusable foam sleeve.
It has onboard storage for all of your attachments, and a blower function to add another cleaning element to your vacuum. This model also comes with a three year warranty
What We Liked
What We Didn't Like
How to Choose the Best Shop Vac for Dust Collection
First off, what criteria should you be looking for in the best shop vacuum for you?
Cord and Hose Length
The first thing that we recommend looking at is both the power cord and hose length. You want to make sure that you have enough distance to be able to plug in your vacuum and clean the entire garage without a shortage in cord or hose.
Ability to Clean up Dust
Since we are taking a look at the best vacuums for cleaning up dust, you want to make sure that the vacuum you are looking for is equipped with powerful enough suction and the right filtration to get your shop clean. Make sure that your vacuum has enough power to suck up the dust and debris in your shop, and the right nozzles and heads to do so.
How big is your workspace? You want to make sure that you have a big enough vacuum container so that you don't have to empty out your vacuum multiple times when cleaning your shop. Make sure that you get a big enough vacuum for your shop space.
So in the end, what's the best value when it comes to the best shop vacuum for dust collection?
This was a really close race for us, but in the end we really liked the Workshop Wet Dry Vacuum the best. When it comes to getting the best bang for your buck, this massive, powerful vacuum offers you absolutely everything that you could need in a quality shop vacuum, at a really reasonable price Workshop is a company that you can trust, that brings another quality shop vacuum to the table. Although, the Dustless Technologies vacuum was a close second, you can't beat the price of the Workshop Wet Dry Vac.