A compact algorithm for rectification of stereo pairs
Machine Vision and Applications
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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International Journal of Computer Vision
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CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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This paper studies the use of temporal consistency to match appearance descriptors and handle complex ambiguities when computing dynamic depth maps from stereo. Previous attempts have designed 3D descriptors over the spacetime volume and have been mostly used for monocular action recognition, as they cannot deal with perspective changes. Our approach is based on a state-of-the-art 2D dense appearance descriptor which we extend in time by means of optical flow priors, and can be applied to wide-baseline stereo setups. The basic idea behind our approach is to capture the changes around a feature point in time instead of trying to describe the spatiotemporal volume. We demonstrate its effectiveness on very ambiguous synthetic video sequences with ground truth data, as well as real sequences.