NDLI: Natural scenes categorization by hierarchical extraction of typicality patterns

Content Provider	IEEE Xplore Digital Library
Author	Perina, A. Cristani, M. Murino, V.
Copyright Year	2007
Description	Author affiliation: Univ. degli Studi di Verona, Verona (Perina, A.; Cristani, M.; Murino, V.)
Abstract	Natural scene categorization of images represents a very useful task for automatic image analysis systems in a wide variety of applications. In the literature, several methods have been proposed facing this issue with excellent results. Typically, features of several types are clustered so as to generate a vocabulary able to efficiently represent the considered image collection. This vocabulary is formed by a discrete set of visual codewords whose co-occurrence or composition allows to classify the scene category. A common drawback of these methods is that features are usually extracted from the whole image, actually disregarding whether they derive from the scene to be classified or other objects, independent from the scene, eventually present in it. As quoted by perceptual studies, features regarding objects present in an image are not useful to scene categorization, indeed bringing an important source of clutter, in dependence of their size. In this paper, a novel, multi- scale, statistical approach for image representation aimed at scene categorization is presented. The method is able to select, at different scales, sets of features that represent exclusively the scene disregarding other non-characteristic, clutter, elements. The proposed procedure, based on a generative model, is then able to produce a robust representation scheme useful for image classification. The obtained results are very convincing and prove the goodness of the approach even by just considering simple features like local color image histograms.
Starting Page	801
Ending Page	806
File Size	945078
Page Count	6
File Format	PDF
ISBN	9780769528779
DOI	10.1109/ICIAP.2007.4362874
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-10
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Layout Prototypes Labeling Vocabulary Feature extraction Image representation Robustness Image databases Spatial databases Visual databases
Content Type	Text
Resource Type	Article

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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
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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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