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Optical Engineering

Object recognition by belief propagation
Author(s): Tongwei Lu; Nong Sang; Jizhong Liu; Xiaoying Gao
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Paper Abstract

We try to incorporate a graphical model to solve the problem of object recognition, which is a fundamental problem in computer vision. Adopting the multiscale feature keypoint technique, we present an object recognition algorithm that establishes the center, scale factor, and rotation angle of the object in the images. First, the local invariant features are detected in template and scene images. Second, the belief propagation algorithm is used to compute the correspondence considering the spatial constraints. Third, each correspondence point records a vote to the object's center, scale factor, and rotation angle. Finally, we keep the densest point on the vote map as the recognition result. Experimental results demonstrate the robustness of the algorithm on real images.

Paper Details

Date Published: 1 July 2008
PDF: 4 pages
Opt. Eng. 47(7) 077205 doi: 10.1117/1.2957950
Published in: Optical Engineering Volume 47, Issue 7
Show Author Affiliations
Tongwei Lu, Huazhong Univ. of Science and Technology (China)
Nong Sang, Huazhong Univ. of Science and Technology (China)
Jizhong Liu, National Lab. of Aerospace Intelligent Control (China)
Xiaoying Gao, National Lab. of Aerospace Intelligent Control (China)


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