NDLI: Object Recognition as Many-to-Many Feature Matching

Content Provider	Springer Nature Link
Author	Demirci, M. Fatih Shokoufandeh, Ali Keselman, Yakov Bretzner, Lars Dickinson, Sven
Copyright Year	2006
Abstract	Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation errors, articulation, scale difference, and within-class deformation can yield image and model features which don’t match one-to-one but rather many-to-many. Adopting a graph-based representation of a set of features, we present a matching algorithm that establishes many-to-many correspondences between the nodes of two noisy, vertex-labeled weighted graphs. Our approach reduces the problem of many-to-many matching of weighted graphs to that of many-to-many matching of weighted point sets in a normed vector space. This is accomplished by embedding the initial weighted graphs into a normed vector space with low distortion using a novel embedding technique based on a spherical encoding of graph structure. Many-to-many vector correspondences established by the Earth Mover’s Distance framework are mapped back into many-to-many correspondences between graph nodes. Empirical evaluation of the algorithm on an extensive set of recognition trials, including a comparison with two competing graph matching approaches, demonstrates both the robustness and efficacy of the overall approach.
Starting Page	203
Ending Page	222
Page Count	20
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	69
Issue Number	2
e-ISSN	15731405
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2006-05-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	graph matching graph embedding Earth Mover’s Distance (EMD) object recognition Pattern Recognition Artificial Intelligence (incl. Robotics) Computer Imaging, Graphics and Computer Vision Image Processing
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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