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一种鲁棒的基于光度立体视觉的表面重建方法

DOI: 10.3724/SP.J.1004.2013.01339, PP. 1339-1348

Keywords: 光度立体视觉,鲁棒主成分分析,表面重建,稀疏噪声,低秩矩阵

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Abstract:

?提出一种基于先进的凸优化技术的光度立体视觉重建框架.首先通过鲁棒的主成分分析(Robustprinciplecomponentanalysis,RPCA)祛除图像噪声,得到低秩矩阵和物体表面向量场,然后再通过表面重建算法从向量场来恢复物体形状.相对于先前的一些使用最小二乘或者一些启发式鲁棒技术的方法,该方法使用了所有可用的信息,可以同时修复数据中的丢失和噪声数据,显示出了较高的计算效率以及对于大的稀疏噪声的鲁棒性.实验结果表明,本文提出的框架大大提高了在噪声存在情况下物体表面的重建精度.

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