PM-Huber: PatchMatch with Huber Regularization for Stereo Matching

Philipp Heise, Sebastian Klose, Brian Jensen, Alois Knoll; The IEEE International Conference on Computer Vision (ICCV), 2013, pp. 2360-2367

Abstract


Most stereo correspondence algorithms match support windows at integer-valued disparities and assume a constant disparity value within the support window. The recently proposed PatchMatch stereo algorithm [7] overcomes this limitation of previous algorithms by directly estimating planes. This work presents a method that integrates the PatchMatch 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.

Related Material


[pdf]
[bibtex]
@InProceedings{Heise_2013_ICCV,
author = {Heise, Philipp and Klose, Sebastian and Jensen, Brian and Knoll, Alois},
title = {PM-Huber: PatchMatch with Huber Regularization for Stereo Matching},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}
}