A multiple-baseline stereo

A stereo matching method is presented which uses multiple stereo pairs with various baselines to obtain precise depth estimates without suffering from ambiguity. The stereo matching method uses multiple stereo pairs with different baselines generated by a lateral displacement of a camera. Matching is performed by computing the sum of squared-difference (SSD) values. The SSD functions for individual stereo pairs are represented with respect to the inverse depth (rather than the disparity, as is usually done), and then are simply added to produce the sum of SSDs. This resulting function is called the SSSD-in-inverse-depth. The authors define a stereo algorithm, based on the SSSD-in-inverse-depth and then present a mathematical analysis to show how the algorithm can remove ambiguity and increase precision. Experimental results for stereo images are presented to demonstrate the effectiveness of the algorithm.<<ETX>>

[1]  T. Poggio,et al.  A computational theory of human stereo vision , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[2]  M. J. Hannah A system for digital stereo image matching , 1989 .

[3]  Hans P. Moravec Visual Mapping by a Robot Rover , 1979, IJCAI.

[4]  W. Eric L. Grimson,et al.  Computational Experiments with a Feature Based Stereo Algorithm , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Masatoshi Okutomi,et al.  A Bayesian Foundation for Active Stereo Vision1 , 1990, Other Conferences.

[6]  Tomaso Poggio,et al.  A Theory of Human Stereo Vision , 1977 .

[7]  Joachim Heel,et al.  Dynamic Motion Vision , 1989, Other Conferences.

[8]  M. Okutomi,et al.  A Bayesian Foundation for Active Stereo Vision , 1989 .

[9]  Masanobu Yamamoto,et al.  The Image Sequence Analysis of Three-Dimensional Dynamic Scenes , 1988 .

[10]  Gérard G. Medioni,et al.  Parallel Multiscale Stereo Matching Using Adaptive Smoothing , 1990, ECCV.

[11]  Roger Y. Tsai,et al.  Multiframe Image Point Matching and 3-D Surface Reconstruction , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.