eprintid: 1339
rev_number: 7
eprint_status: archive
userid: 6
dir: disk0/00/00/13/39
datestamp: 2012-09-04 09:57:02
lastmod: 2012-09-04 09:57:02
status_changed: 2012-09-04 09:57:02
type: article
metadata_visibility: show
creators_name: Casalino, Gabriella
creators_name: Del Buono, Nicoletta
creators_name: Minervini, Massimo
creators_id: 
creators_id: 
creators_id: massimo.minervini@imtlucca.it
title: Nonnegative Matrix Factorizations Performing Object Detection and Localization
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: public
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.
date: 2012
date_type: published
publication: Applied Computational Intelligence and Soft Computing
volume: 2012
publisher: Hindawi Publishing Corporation
pagerange: 1-19
id_number: 10.1155/2012/781987
refereed: TRUE
issn: 1687-9724
official_url: http://dx.doi.org/10.1155/2012/781987
citation:   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)  
document_url: http://eprints.imtlucca.it/1339/1/Applied%20Computational%20Intelligence%20and%20Soft%20Computing_Minervini.pdf