Nonnegative Matrix Factorizations Performing Object Detection and Localization. (24th June 2012)

• Record Type: Journal Article
• Authors: Casalino, G.; Del Buono, N.; Minervini, M.
• Other Names: Janikow Cezary Z. Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2012(2012)
• Publication Date: 2012-06-24
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2012/781987
• Languages: English
• ISSNs: 1687-9724

Abstract

Abstract : 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.