Some Properties of the E Matrix in Two-View Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Artificial Intelligence - Special volume on computer vision
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Epipolar geometry of central panoramic catadioptric cameras
Panoramic vision
Epipolar Geometry of Panoramic Cameras
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A Unifying Theory for Central Panoramic Systems and Practical Applications
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
A Complete Panoramic Vision System, Incorporating Imaging, Ranging, and Three Dimensional Navigation
OMNIVIS '00 Proceedings of the IEEE Workshop on Omnidirectional Vision
Reliable 3D Reconstruction from a Few Catadioptric Images
OMNIVIS '02 Proceedings of the Third Workshop on Omnidirectional Vision
A Space Variant Gradient Based Corner Detector for Sparse Omnidirectional Images
Journal of Mathematical Imaging and Vision
Two novel real-time local visual features for omnidirectional vision
Pattern Recognition
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Active matching windows for matching in panoramic images taken by a catadioptric camera are proposed. The shape and the size of the windows vary depending on the position of an interest point. The windows size is then normalized and a standard correlation is used for measuring similarities of the points. A semi-iterative method based on sorting correspondences according to their similarity is suggested to remove possible outliers. It is experimentally shown that using this method the matching is successful for small and also big displacement of corresponding points.