Using Models to Improve Stereo Reconstruction

Authors:
Henri Maître;Wei Luo
Affiliations:
-;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Year:
1992

Citing 6
Cited 0

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Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

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Abstract

The authors propose the combination of photometric and stereometric information to solve the stereo vision problem in the case of a man-made environment. A method to introduce geometrical models in the stereo process in order to improve the accuracy of the depth measurement and to extend the depth map to points where no measurements have been made is presented. This method is based on a parameterization of the object surfaces and relies on a systematic comparison of the result of a stereo process with the photometric (or gray-level) image. The proposed approach improves the accuracy of the stereo information and its density by introducing a hypothesis on the object surfaces. Two kinds of hypothesis are developed: planar and quadratic objects. Reconstructions of complex scenes are given.