CVFX Lecture 15: Stereo correspondence

ECSE-6969 Computer Vision for Visual Effects
Rich Radke, Rensselaer Polytechnic Institute
Lecture 15: Stereo correspondence (3/20/14)
0:00:01 Stereo correspondence
0:02:09 Disparity
0:04:43 Differences between stereo and optical flow
0:11:42 Basic stereo algorithms
0:12:04 Sum of absolute differences
0:14:27 Birchfield-Tomasi measure
0:16:31 Census transform
0:20:46 Dynamic programming for stereo
0:25:19 Non-monotonic correspondence
0:26:53 The Ohta-Kanade algorithm
0:29:31 Stereo algorithm benchmarking
0:36:21 Graph cuts for stereo
0:52:07 Belief propagation for stereo
0:56:02 Occlusions and discontinuities
0:59:53 Incorporating segmentation
1:06:50 Stereo rigs for filming
Follows Section 5.5 of the textbook. cvfxbook.com
Key references:
D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1):7--42, Apr. 2002.
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Y. Ohta and T. Kanade. Stereo by intra- and inter-scanline search using dynamic programming. IEEE Transactions on Pattern Analysis and Machine Intelligence, 7(2):139--54, Mar. 1985.
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Y. Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(11):1222--39, Nov. 2001.
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J. Sun, N.-N. Zheng, and H.-Y. Shum. Stereo matching using belief propagation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(7):787--800, July 2003.
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