A performance study on different cost aggregation approaches used in real-time stereo matching

Many vision applications require high-accuracy dense disparity maps in real-time and online. Due to time constraint, most real-time stereo applications rely on local winner-takes-all optimization in the disparity computation process. These local approaches are generally outperformed by offline globa...

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Bibliographic Details
Published in:International journal of computer vision 2007-11, Vol.75 (2), p.283-296
Main Authors: Gong, Minglun, Yang, Ruigang, Wang, Liang, Gong, Mingwei
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Optimization techniques
Pattern recognition. Digital image processing. Computational geometry
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Summary:Many vision applications require high-accuracy dense disparity maps in real-time and online. Due to time constraint, most real-time stereo applications rely on local winner-takes-all optimization in the disparity computation process. These local approaches are generally outperformed by offline global optimization based algorithms. However, recent research shows that, through carefully selecting and aggregating the matching costs of neighboring pixels, the disparity maps produced by a local approach can be more accurate than those generated by many global optimization techniques. We are therefore motivated to investigate whether these cost aggregation approaches can be adopted in real-time stereo applications and, if so, how well they perform under the real-time constraint. The evaluation is conducted on a real-time stereo platform, which utilizes the processing power of programmable graphics hardware. Six recent cost aggregation approaches are implemented and optimized for graphics hardware so that real-time speed can be achieved. The performances of these aggregation approaches in terms of both processing speed and result quality are reported.[PUBLICATION ABSTRACT]
ISSN:0920-5691
1573-1405
DOI:10.1007/s11263-006-0032-x