A block-based clustering technique for real time object detection on a static background

Alexandropoulos, T; Loumos, V; Kayafas, E

dc.contributor.author	Alexandropoulos, T	en
dc.contributor.author	Loumos, V	en
dc.contributor.author	Kayafas, E	en
dc.date.accessioned	2014-03-01T02:42:23Z
dc.date.available	2014-03-01T02:42:23Z
dc.date.issued	2004	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30972
dc.subject	Indoor surveillance	en
dc.subject	Object detection	en
dc.subject	Static background	en
dc.subject.other	Color	en
dc.subject.other	Decision theory	en
dc.subject.other	Image analysis	en
dc.subject.other	Problem solving	en
dc.subject.other	Robustness (control systems)	en
dc.subject.other	Statistical methods	en
dc.subject.other	Block-based clustering technique	en
dc.subject.other	Indoor surveillance	en
dc.subject.other	Object detection	en
dc.subject.other	Static background	en
dc.subject.other	Object recognition	en
dc.title	A block-based clustering technique for real time object detection on a static background	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IS.2004.1344659	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IS.2004.1344659	en
heal.publicationDate	2004	en
heal.abstract	Block-based statistic methods for object detection are used as tools for fast object discrimination. However, their performance degrades when it comes to image alterations of a large scale. This paper presents a block-based clustering technique applied on blocks of the absolute difference. The proposed method presents the additional benefit of increased robustness against large-scale image alterations. Two variations of the algorithm are presented: one applied on grayscale image pairs and one exploiting chromatic variations in color images.	en
heal.journalName	2004 2nd International IEEE Conference 'Intelligent Systems' - Proceedings	en
dc.identifier.doi	10.1109/IS.2004.1344659	en
dc.identifier.volume	1	en
dc.identifier.spage	169	en
dc.identifier.epage	173	en