Paper
25 March 2003 Stereo-matching approach based on wavelet analysis for 3D reconstruction in neurovision system
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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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yingen Xiong "Stereo-matching approach based on wavelet analysis for 3D reconstruction in neurovision system", Proc. SPIE 5015, Applications of Artificial Neural Networks in Image Processing VIII, (25 March 2003); https://doi.org/10.1117/12.477385
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Cited by 2 scholarly publications.
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KEYWORDS
Wavelets

Neural networks

3D image reconstruction

3D modeling

3D image processing

Image processing

Computing systems

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