NDLI: Enhancing Stereo Matching With Classification

Content Provider	IEEE Xplore Digital Library
Author	Baydoun, M. Al-Alaoui, M.A.
Copyright Year	2013
Abstract	This paper presents a novel approach that employs classification to enhance the accuracy of the stereo matching problem. First, the images are treated in order to improve their pixel to pixel correspondence and reduce illumination differences. After that, stereo matching is addressed using different methods with emphasis on local ones like the sum of absolute distances and normalized cross correlation. Other state-of-the-art approaches are also considered. Then, and for every pixel, different features are computed from the input stereo image and the initially found depth map. Afterward, boosting and neural networks, as classification methods, are used to handle occlusion and enhance stereo matching by finding the erroneous disparity values. These values are then corrected through a completion stage. The accuracy of the proposed implementation improves on the problem in an efficient manner. A timing analysis of the method is provided to validate the real time performance. This paper further clarifies some of the possible developments based on various discussions.
Starting Page	485
Ending Page	499
Page Count	15
File Size	7538670
File Format	PDF
ISSN	21693536
Volume Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	IEEE standards Real-time systems Classification Stereo matching real time classification
Content Type	Text
Resource Type	Article
Subject	Computer Science Engineering Materials Science

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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