Abstract
This paper presents a region-based stereo matching algorithm which uses a new method to select the final disparity: a random process computes for each pixel different approximations of its disparity relying on a surface model with different image segmentations and each found disparity gets a vote. At last, the final disparity is selected by estimating the mode of a density function built from these votes. We also advise how to choose the different parameters. Finally, an evaluation shows that the proposed method is efficient even at sub-pixel accuracy and is competitive with the state of the art.
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Gales, G., Crouzil, A., Chambon, S. (2010). A Region-Based Randomized Voting Scheme for Stereo Matching. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_18
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DOI: https://doi.org/10.1007/978-3-642-17274-8_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17273-1
Online ISBN: 978-3-642-17274-8
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