Abstract
Area-based stereo matching algorithms are based on the support of a surrounding area to establish a point-to-point correspondence in two images. Two important problems arise in this context: How to obtain subpixel information and how to choose the optimal surrounding area.
In this paper we present a non-iterative two-step algorithm for subpixel accurate stereo matching by using an adaptive window. In contrast to existing algorithms the window is not restricted to a rectangle but can be of any general shape. Starting from an initial sparse disparity estimate, the first step is to find the general shape of the window. This is performed by estimating the local disparity of each pixel in a box of maximum size using a bank of Gabor filters, and by applying a consistency constraint. In the second step the projective distortion is computed using the masked window. The performed experiments show the accurate and robust behavior of the proposed algorithm.
This work was supported by the Austrian Science Foundation (FWF) under grant P12278-MAT.
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© 1999 Springer-Verlag Berlin Heidelberg
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Werth, P., Scherer, S., Pinz, A. (1999). Subpixel Stereo Matching by Robust Estimation of Local Distortion Using Gabor Filters. In: Solina, F., Leonardis, A. (eds) Computer Analysis of Images and Patterns. CAIP 1999. Lecture Notes in Computer Science, vol 1689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48375-6_76
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DOI: https://doi.org/10.1007/3-540-48375-6_76
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