Efficient tracking using a robust motion estimation technique

Lalos, C; Voulodimos, A; Doulamis, A; Varvarigou, T

dc.contributor.author	Lalos, C	en
dc.contributor.author	Voulodimos, A	en
dc.contributor.author	Doulamis, A	en
dc.contributor.author	Varvarigou, T	en
dc.date.accessioned	2014-03-01T11:46:54Z
dc.date.available	2014-03-01T11:46:54Z
dc.date.issued	2012	en
dc.identifier.issn	13807501	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/38036
dc.subject	Motion estimation	en
dc.subject	Object tracking	en
dc.subject	Temporal inference	en
dc.title	Efficient tracking using a robust motion estimation technique	en
heal.type	other	en
heal.identifier.primary	10.1007/s11042-012-0994-3	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s11042-012-0994-3	en
heal.publicationDate	2012	en
heal.abstract	Camera based supervision is a critical part of event detection and analysis applications. However, visual tracking still remains one of the biggest challenges in the area of computer vision, although it has been extensively discussed during in the previous years. In this paper we propose a robust tracking approach based on object flow, which is a motion model for estimating both the displacement and the direction of an object of interest. In addition, an observation model that utilizes a generative prior is adopted to tackle the pitfalls that derive from the appearance changes of the object under study. The efficiency of our technique is demonstrated using sequences captured in a complex industrial environment. The experimental results show that the proposed algorithm is sound, yielding improved performance in comparison with other tracking approaches. © 2012 Springer Science+Business Media, LLC.	en
heal.journalName	Multimedia Tools and Applications	en
dc.identifier.doi	10.1007/s11042-012-0994-3	en
dc.identifier.spage	1	en
dc.identifier.epage	16	en