首页> 外文会议>Conference on Applications of Artificial Neural Networks in Image Processing VIII Jan 23-24, 2003 Santa Clara, California, USA >Stereo matching approach based on wavelet analysis for 3D reconstruction in neurovision system
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Stereo matching approach based on wavelet analysis for 3D reconstruction in neurovision system

机译:基于小波分析的立体匹配方法在神经视觉系统中进行3D重建

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摘要

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.
机译:本文提出了一种基于小波分析的立体匹配3D重建方法。可用于神经视觉系统。该方法可以分为两个部分。首先,通过小波分析解决立体匹配问题。该过程采用二元离散小波分析,并通过全局优化实现了立体匹配过程。构建了一种相干的分层匹配策略,以便可以使用粗略到精细的技术来完成立体声匹配过程。其次,利用BP神经网络构造了3D对象重建神经网络。通过在立体图像对中馈送左图像和右图像之间的图像对应点,可以使用此神经网络获得对象表面上点的3D坐标,并可以重建对象的配置和形状。利用多个3D重建神经网络,可以并行执行3D重建过程。实验中显示了合成图像和真实图像的示例,并获得了良好的结果。

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