Determining straight line correspondences from intensity images
Pattern Recognition
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Artificial Intelligence - Special volume on computer vision
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Multiview Constraints on Homographies
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Multi View Reconstruction and Camera Recovery Using a Reference Plane
International Journal of Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Proceedings of the International Conference on Advances in Computing, Communication and Control
Fast pose estimation for visual navigation using homographies
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Topological maps based on graphs of planar regions
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Distributed multi-camera visual mapping using topological maps of planar regions
Pattern Recognition
Line image signature for scene understanding with a wearable vision system
Proceedings of the 4th International SenseCam & Pervasive Imaging Conference
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This paper addresses the computation of the fundamental matrix between two views, when camera motion and 3D structure are unknown, but planar surfaces can be assumed. We use line features which are automatically matched in two steps. Firstly, with image based parameters, a set of matches are obtained to secondly compute homographies, which allows to reject wrong ones, and to grow good matches in a final stage. The inclusion of projective transformations gives much better results to match features with short computing overload. When two or more planes are observed, different homographies can be computed, segmenting simultaneously the corresponding planar surfaces. These can be used to obtain the fundamental matrix, which gives constraints for the whole scene. The results show that the global process is robust enough, turning out stable and useful to obtain matches and epipolar geometry from lines in man made environments.