NDLI: Matching images more efficiently with local descriptors

Content Provider	IEEE Xplore Digital Library
Author	Dong Zhang Weiqiang Wang Qingming Huang Shuqiang Jiang Wen Gao
Copyright Year	2008
Description	Author affiliation: Key Lab. of Intell. Info. Process., Chin. Acad. of Sci., Beijing (Shuqiang Jiang; Wen Gao) \|\| Grad. Univ. of Chinese Acad. of Sci., Beijing (Dong Zhang; Weiqiang Wang; Qingming Huang)
Abstract	Image matching is a fundamental task for many applications of computer vision. Today it is very popular to represent two matched images as two bags of local descriptors, and the classic RANSAC based matching procedure is always exploited in the task. In this paper, we present a much efficient image matching approach based on sets of any local descriptors. A block-to-block strategy is devised to speed up the establishment of local correspondences. Additionally, the weighted RANSAC (w-RANSAC) technique is proposed to make the search of optimal global models converge faster. Comparative experiments with the RANSAC based paradigm show our approach can not only generate more accurate correspondences, but also double the matching speed.
Starting Page	1
Ending Page	4
File Size	231331
Page Count	4
File Format	PDF
ISBN	9781424421749
ISSN	10514651
DOI	10.1109/ICPR.2008.4761304
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image matching Principal component analysis Lighting Application software Computer vision Image converters Histograms Robustness Shape Digital images
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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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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