Casalino, Gabriella and Del Buono, Nicoletta and Minervini, Massimo Nonnegative Matrix Factorizations Performing Object Detection and Localization. Applied Computational Intelligence and Soft Computing, 2012. pp. 1-19. ISSN 1687-9724 (2012)
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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.
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Research Area:||Computer Science and Applications|
|Depositing User:||Ms T. Iannizzi|
|Date Deposited:||04 Sep 2012 09:57|
|Last Modified:||04 Sep 2012 09:57|
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