NDLI: A Quantitative Evaluation of Confidence Measures for Stereo Vision

Content Provider	IEEE Xplore Digital Library
Author	Xiaoyan Hu Mordohai, P.
Copyright Year	1979
Abstract	We present an extensive evaluation of 17 confidence measures for stereo matching that compares the most widely used measures as well as several novel techniques proposed here. We begin by categorizing these methods according to which aspects of stereo cost estimation they take into account and then assess their strengths and weaknesses. The evaluation is conducted using a winner-take-all framework on binocular and multibaseline datasets with ground truth. It measures the capability of each confidence method to rank depth estimates according to their likelihood for being correct, to detect occluded pixels, and to generate low-error depth maps by selecting among multiple hypotheses for each pixel. Our work was motivated by the observation that such an evaluation is missing from the rapidly maturing stereo literature and that our findings would be helpful to researchers in binocular and multiview stereo.
Sponsorship	IEEE Computer Society
Page Count	13
File Size	2197440
Starting Page	2121
Ending Page	2133
File Format	PDF
ISSN	01628828
Volume Number	34
Issue Number	11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cost function Estimation Reliability Error analysis Stereo image processing Benchmark testing Pattern matching distinctiveness Stereo vision 3D reconstruction confidence correspondence
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Computational Theory and Mathematics Computer Vision and Pattern Recognition Software

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