PM-Huber: PatchMatch with Huber Regularization for Stereo Matching

Computer Vision(2013)

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摘要
Most stereo correspondence algorithms match support windows at integer-valued disparities and assume a constant disparity value within the support window. The recently proposed Patch Match stereo algorithm by Bleyer et al. overcomes this limitation of previous algorithms by directly estimating planes. This work presents a method that integrates the Patch Match stereo algorithm into a variational smoothing formulation using quadratic relaxation. The resulting algorithm allows the explicit regularization of the disparity and normal gradients using the estimated plane parameters. Evaluation of our method in the Middlebury benchmark shows that our method outperforms the traditional integer-valued disparity strategy as well as the original algorithm and its variants in sub-pixel accurate disparity estimation.
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关键词
image matching,smoothing methods,stereo image processing,Huber regularization,Middlebury benchmark,PM-Huber,PatchMatch stereo algorithm,estimated plane parameters,integer-valued disparities,integer-valued disparity strategy,match support windows,quadratic relaxation,stereo correspondence algorithms,stereo matching algorithms,sub-pixel accurate disparity estimation,variational smoothing formulation,PatchMatch,quadratic relaxation,second-order prior,subpixel stereo matching,variational formulation
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