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Prediction of stereo disparity using optical flow
Author(s) -
Paul Beardsley,
J. Michael Brady,
David W. Murray
Publication year - 1990
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.4.46
Subject(s) - computer vision , epipolar geometry , artificial intelligence , optical flow , computer science , orientation (vector space) , matching (statistics) , computer stereo vision , correspondence problem , motion estimation , motion (physics) , stereopsis , mathematics , image (mathematics) , geometry , statistics
This paper describes a scheme in which optical flow information is used to guide stereo correspondence matching. The epipolar constraint, which is used in static stereo to confine correspondence search to a line, is replaced by a mechanism which confines search to an area around a point. The experimental setup consists of a pair of cameras mounted on a mobile robot vehicle. A sequence of stereo image pairs is taken during vehicle motion, and the images are processed by a corner detector. One of the first steps in extracting useful information from the corners is to solve the correspondence problem. For a stereo sequence, this requires both the temporal matching of corners along the sequence, and also the stereo matching of corners between left and right images. The results of the temporal matching (which is easier than the stereo matching) are used to guide the stereo matching. The cameras are assumed to lie in a plane perpendicular to the direction of straight-forward motion, but no other assumptions are made about their orientation, and no knowledge of their extrinsic parameters need be provided as input to the system. The system is currently limited to straight translational motion in a static scene.

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