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Image-Based Localisation in Urban Environments

In this master thesis a method for image-based localisation given a 3D-model of an urban environment is presented. In order to solve the localisation task, a 3D model needs to be constructed. Photos are taken with a calibrated camera of a part of a street from different angles and distances. For the system, the photos are to be matched together in pairs of two, and several 3D-models are built of these pairs. These 3D-models are then concatenated, so they represent one part of a street. The localisation is performed by comparing new images to the model. These photos are also taken with calibrated cameras. Corresponding points between the new image and the model are found using scale invariant discriminate features, called SIFT. The camera location is then determined relative the model. To test the system, the reprojection error is computed for the found correspondences between the image and the model. The results show that the localisation from the 3Dmodel can be done with good result.