NDLI: Loose shape model for discriminative learning of object categories

Content Provider	IEEE Xplore Digital Library
Author	Osadchy, M. Morash, E.
Copyright Year	2008
Description	Author affiliation: Comput. Sci. Dept., Univ. of Haifa, Haifa (Osadchy, M.; Morash, E.)
Abstract	We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent images as a collection of parts characterized by an appearance codeword from a visual vocabulary and by a neighborhood context, organized in an ordered set of bag-of-features representations. These bags are computed in a local overlapping areas around the part. A semantic distance between images is obtained by matching parts associated with the same codeword using their context distributions. The classification is done using SVM with the kernel obtained from the proposed distance. The experiments show that our method outperforms all the classification methods from the PASCAL challenge on half of the VOC2006 categories and has the best average EER. It also outperforms the constellation model learned via boosting, as proposed by Bar-Hillel et al. on their data set, which contains more rigid objects.
Starting Page	1
Ending Page	6
File Size	531343
Page Count	6
File Format	PDF
ISBN	9781424422425
ISSN	10636919
DOI	10.1109/CVPR.2008.4587601
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Solid modeling Vocabulary Support vector machines Support vector machine classification Kernel Dogs Computer science Boosting Polynomials
Content Type	Text
Resource Type	Article
Subject	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
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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