Stereo Error Detection, Correction, and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Belief Propagation for Stereo Analysis of Night-Vision Sequences
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Stereo by two-level dynamic programming
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Integrating disparity images by incorporating disparity rate
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Illumination invariant cost functions in semi-global matching
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
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Stereo and motion analysis are potential techniques for providing information for control or assistance systems in various robotics or driver assistance applications. This paper evaluates the performance of several stereo and motion algorithms over a long synthetic sequence (100 stereo pairs). Such an evaluation of low-level computer vision algorithms is necessary, as moving platforms are being used for image analysis in a wide area of applications. In this paper algorithms are evaluated with respect to robustness by modifying the test sequence with various types of realistic noise. The novelty of this paper is comparing top performing algorithms on a long sequence of images, taken from a moving platform.