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Proceedings Paper

Stereo-matching approach based on wavelet analysis for 3D reconstruction in a neurovision system
Author(s): Yingen Xiong
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Paper Abstract

In this paper, a stereo matching approach for 3D reconstruction based on wavelet analysis is presented. It can be used in neuro-vision system. The approach can be divided into two parts. First, the stereo matching problem is solved with wavelet analysis. Dyadic discrete wavelet analysis is adopted in this process and stereo matching process is realized with global optimization. A coherent hierarchical matching strategy is constructed, so that the stereo matching process can be accomplished with coarse to fine techniques. Second, a 3D object reconstruction neural network is constructed by using BP neural network. By feeding the image corresponding points between the left image and right image in a stereo image pair, the 3D coordinates of points on object surface can be obtained using this neural network and the configuration and shape of the object can be reconstructed. With multiple 3D reconstruction neural networks the 3D reconstruction processes can be performed in parallel. The examples for both synthetic and real images are shown in the experiment, and good results are obtained.

Paper Details

Date Published: 25 March 2003
PDF: 6 pages
Proc. SPIE 5015, Applications of Artificial Neural Networks in Image Processing VIII, (25 March 2003); doi: 10.1117/12.477385
Show Author Affiliations
Yingen Xiong, Wright State Univ. (United States)


Published in SPIE Proceedings Vol. 5015:
Applications of Artificial Neural Networks in Image Processing VIII
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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