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Stereo correspondence using efficient hierarchical belief propagation

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Abstract

In this paper, a new algorithm is presented to compute the disparity map from a stereo pair of images by using Belief Propagation (BP). While many algorithms have been proposed in recent years, the real-time computation of an accurate disparity map is still a challenging task. The computation time and run-time memory requirements are two very important factors for all real-time applications. The proposed algorithm divides the matching process into two steps; they are initial matching and disparity map refinement. Initial matching is performed by memory efficient hierarchical belief propagation algorithm that uses less than half memory at run-time and minimizes the energy function at much faster rate as compare to other hierarchical BP algorithms that makes it more suitable for real-time applications. Disparity map refinement uses a simple but very effective single-pass approach that improves the accuracy without affecting the computation cost. Experiments by using Middlebury dataset demonstrate that the performance of our algorithm is the best among other real-time stereo matching algorithms.

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Acknowledgments

The author would like to thank Daniel Scharstein and Richard Szeliski for making stereo images with ground truth data available.

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Authors and Affiliations

  1. Forensics and Security Lab, School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore, 639798, Singapore

    Raj Kumar Gupta & Siu-Yeung Cho

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  1. Raj Kumar Gupta
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  2. Siu-Yeung Cho
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Correspondence to Siu-Yeung Cho.

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Gupta, R.K., Cho, SY. Stereo correspondence using efficient hierarchical belief propagation. Neural Comput & Applic 21, 1585–1592 (2012). https://doi.org/10.1007/s00521-012-0831-7

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  • DOI: https://doi.org/10.1007/s00521-012-0831-7

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