research-article

Near Real-Time Stereo Matching Using Geodesic Diffusion

Authors:

Leonardo De-Maeztu,

Arantxa Villanueva,

Rafael CabezaAuthors Info & Claims

IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 34, Issue 2

Pages 410 - 416

https://doi.org/10.1109/TPAMI.2011.192

Published: 01 February 2012 Publication History

Abstract

Adaptive-weight algorithms currently represent the state of the art in local stereo matching. However, due to their computational requirements, these types of solutions are not suitable for real-time implementation. Here, we present a novel aggregation method inspired by the anisotropic diffusion technique used in image filtering. The proposed aggregation algorithm produces results similar to adaptive-weight solutions while reducing the computational requirements. Moreover, near real-time performance is demonstrated with a GPU implementation of the algorithm.

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Choi OChang H(2016)Yet Another Cost Aggregation Over ModelsIEEE Transactions on Image Processing10.1109/TIP.2016.259929525:11(5397-5410)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1109/TIP.2016.2599295
Dongming Chen Ardabilian MLiming Chen (2015)A Fast Trilateral Filter-Based Adaptive Support Weight Method for Stereo MatchingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2014.236142225:5(730-743)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.1109/TCSVT.2014.2361422
Der-Wei Yang Li-Chia Chu Chun-Wei Chen Jonas Wang Ming-Der Shieh (2015)Depth-Reliability-Based Stereo-Matching Algorithm and Its VLSI Architecture DesignIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2014.236141925:6(1038-1050)Online publication date: 2-Jun-2015
https://dl.acm.org/doi/10.1109/TCSVT.2014.2361419
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cover image IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 34, Issue 2

February 2012

208 pages

ISSN:0162-8828

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IEEE Computer Society

United States

Publication History

Published: 01 February 2012

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Choi OChang H(2016)Yet Another Cost Aggregation Over ModelsIEEE Transactions on Image Processing10.1109/TIP.2016.259929525:11(5397-5410)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1109/TIP.2016.2599295
Dongming Chen Ardabilian MLiming Chen (2015)A Fast Trilateral Filter-Based Adaptive Support Weight Method for Stereo MatchingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2014.236142225:5(730-743)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.1109/TCSVT.2014.2361422
Der-Wei Yang Li-Chia Chu Chun-Wei Chen Jonas Wang Ming-Der Shieh (2015)Depth-Reliability-Based Stereo-Matching Algorithm and Its VLSI Architecture DesignIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2014.236141925:6(1038-1050)Online publication date: 2-Jun-2015
https://dl.acm.org/doi/10.1109/TCSVT.2014.2361419
Pham CDinh VJeon J(2015)Robust non-local stereo matching for outdoor driving images using segment-simple-treeImage Communication10.1016/j.image.2015.09.01239:PA(173-184)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1016/j.image.2015.09.012
Shan YHao YWang WWang YChen XYang HLuk W(2014)Hardware Acceleration for an Accurate Stereo Vision System Using Mini-Census Adaptive Support RegionACM Transactions on Embedded Computing Systems10.1145/258465913:4s(1-24)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1145/2584659
Jin MMaruyama T(2014)Fast and Accurate Stereo Vision System on FPGAACM Transactions on Reconfigurable Technology and Systems10.1145/25676597:1(1-24)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1145/2567659
Tan XSun CSirault XFurbank RPham T(2014)Stereo matching using cost volume watershed and region mergingImage Communication10.1016/j.image.2014.06.00229:10(1232-1244)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1016/j.image.2014.06.002

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