NDLI: Stereo correspondence using efficient hierarchical belief propagation

Content Provider	Springer Nature Link
Author	Gupta, Raj Kumar Cho, Siu Yeung
Copyright Year	2012
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.
Starting Page	1585
Ending Page	1592
Page Count	8
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	21
Issue Number	7
e-ISSN	14333058
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-01-22
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Stereo vision Hierarchical belief propagation Disparity map refinement Simulation and Modeling
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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