DocumentCode
3426462
Title
PM-Huber: PatchMatch with Huber Regularization for Stereo Matching
Author
Heise, Peter ; Klose, Sebastian ; Jensen, Bjoern ; Knoll, Aaron
Author_Institution
Dept. of Inf., Tech. Univ. Munchen, München, Germany
fYear
2013
fDate
1-8 Dec. 2013
Firstpage
2360
Lastpage
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 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.
Keywords
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; Benchmark testing; Cameras; Equations; Mathematical model; Minimization; Smoothing methods; Stereo vision; PatchMatch; quadratic relaxation; second-order prior; subpixel stereo matching; variational formulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location
Sydney, NSW
ISSN
1550-5499
Type
conf
DOI
10.1109/ICCV.2013.293
Filename
6751404
Link To Document