This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Stereo Correspondence with Compact Windows via Minimum Ratio Cycle
December 2002 (vol. 24 no. 12)
pp. 1654-1660

Abstract—One of the earliest and still widely used methods for dense stereo correspondence is based on matching windows of pixels. The main difficulty of this method is choosing a window of appropriate size and shape. Small windows may lack sufficient intensity variation for reliable matching, while large windows smooth out disparity discontinuities. We propose an algorithm to choose a window size and shape by optimizing over a large class of "compact" windows. The word compact is used informally to reflect the fact that the ratio of perimeter to area of our windows is small. We believe that this is the first area based method which efficiently constructs nonrectangular windows. Fast optimization over compact windows is achieved via the minimum ratio cycle algorithm for graphs. The algorithm has only a few parameters which are easy to fix.

[1] K. Ahuja, T.L. Magnati, and J.B. Orlin, Network Flows: Theory, Algorithms, and Applications. Prentice Hall, 1993.
[2] A.F. Bobick and S.S. Intille, “Large Occlusion Stereo,” Vismod, 1999.
[3] O. Faugeras, B. Hotz, H. Mathieu, T. Viéville, Z. Zhang, P. Fua, E. Théron, L. Moll, G. Berry, J. Vuillemin, P. Bertin, and C. Proy, “Real Time Correlation-Based Stereo: Algorithm, Implementatinos and Applications,” Technical Report 2013, INRIA, 1993.
[4] A. Fusiello and V. Roberto, “Efficient Stereo with Multiple Windowing,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 858-863, 1997.
[5] D. Geiger, B. Ladendorf, and A. Yuille, “Occlusions and Binocular Stereo,” Int'l J. Computer Vision, vol. 14, pp. 211-226, 1995.
[6] D.B. Gennery, “Modelling the Environment of an Exploring Vehicle by Means of Stereo Vision.” 1980.
[7] M.J. Hannah, “Computer Matching of Areas in Stereo Imagery.” PhD thesis, 1978.
[8] I. Jermyn and H. Ishikawa, “Globally Optimal Regions and Boundaries as Minimum Ratio Cycles,” IEEE Trans. Pattern Analysis and Machine Intelligence, 2001.
[9] T. Kanade and M. Okutomi, “A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, pp. 920-932, 1994.
[10] E. Lawler, “Optimal Cycles in Doubly Weighted Directed Linear Graphs,” Proc. Int'l Symp. Theory of Graphs, pp. 209-232, Gordon and Breach, 1966.
[11] M.D. Levine, D.A. O'Handley, and G.M. Yagi, “Computer Determination of Depth Maps,” Proc. CGIP, vol. 2, pp. 131-150, 1973.
[12] K. Mori, M. Kidode, and H. Asada, “An Iterative Prediction and Correction Method for Automatic Stereocomparison,” Proc. CGIP, vol. 2, pp. 393-401, 1973.
[13] D.J. Panton, “A Flexible Approach to Digital Stereo Mapping,” J. Photogrammetric Eng., vol. 44, no. 12, pp. 1499-1512, Dec. 1978.
[14] D. Scharstein and R. Szeliski, “A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms,” IJCV, vol. 47, no. 1-3, pp. 7-42, Apr. 2002.
[15] S. Scherer, W. Andexer, and A. Pinz, “Robust Adaptive Window Matching by Homogeneity Constraint and Integration of Descriptions,” Proc. Int'l Conf. Pattern Recognition, p. 1, 1998.
[16] N. Sebe, M.S. Lew, and D.P. Huijsmans, “Toward Improved Ranking Metrics,” IEEE Trans. Pattern and Machine Intelligence, vol. 22, no. 10, pp. 1132-1143, Oct. 2000.
[17] O. Veksler, “Stereo Correspondence with Compact Windows via Minimum Ratio Cycle,” NEC Research Institute technical report, 2001.

Index Terms:
Stereo correspondence, adaptive windows, compact windows, minimum ratio cycle, graph algorithms.
Citation:
Olga Veksler, "Stereo Correspondence with Compact Windows via Minimum Ratio Cycle," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 12, pp. 1654-1660, Dec. 2002, doi:10.1109/TPAMI.2002.1114859
Usage of this product signifies your acceptance of the Terms of Use.