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Nonnegative Matrix Factorizations Performing Object Detection and Localization
Joint Authors
Minervini, M.
Casalino, G.
Del Buono, N.
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-06-24
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Information Technology and Computer Science
Abstract EN
We study the problem of detecting and localizing objects in still, gray-scale images making use of the part-based representation provided by nonnegative matrix factorizations.
Nonnegative matrix factorization represents an emerging example of subspace methods, which is able to extract interpretable parts from a set of template image objects and then to additively use them for describing individual objects.
In this paper, we present a prototype system based on some nonnegative factorization algorithms, which differ in the additional properties added to the nonnegative representation of data, in order to investigate if any additional constraint produces better results in general object detection via nonnegative matrix factorizations.
American Psychological Association (APA)
Casalino, G.& Del Buono, N.& Minervini, M.. 2012. Nonnegative Matrix Factorizations Performing Object Detection and Localization. Applied Computational Intelligence and Soft Computing،Vol. 2012, no. 2012, pp.1-19.
https://search.emarefa.net/detail/BIM-497570
Modern Language Association (MLA)
Casalino, G.…[et al.]. Nonnegative Matrix Factorizations Performing Object Detection and Localization. Applied Computational Intelligence and Soft Computing No. 2012 (2012), pp.1-19.
https://search.emarefa.net/detail/BIM-497570
American Medical Association (AMA)
Casalino, G.& Del Buono, N.& Minervini, M.. Nonnegative Matrix Factorizations Performing Object Detection and Localization. Applied Computational Intelligence and Soft Computing. 2012. Vol. 2012, no. 2012, pp.1-19.
https://search.emarefa.net/detail/BIM-497570
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-497570