A snake model for object tracking in natural sequences

Tsechpenakis, G; Rapantzikos, K; Tsapatsoulis, N; Kollias, S

dc.contributor.author	Tsechpenakis, G	en
dc.contributor.author	Rapantzikos, K	en
dc.contributor.author	Tsapatsoulis, N	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:19:48Z
dc.date.available	2014-03-01T01:19:48Z
dc.date.issued	2004	en
dc.identifier.issn	0923-5965	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15718
dc.subject	Active contours	en
dc.subject	Cluttered sequences	en
dc.subject	Occlusion	en
dc.subject	Snakes	en
dc.subject	Tracking	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Automation	en
dc.subject.other	Computational complexity	en
dc.subject.other	Computer vision	en
dc.subject.other	Mathematical models	en
dc.subject.other	Motion estimation	en
dc.subject.other	Motion pictures	en
dc.subject.other	Real time systems	en
dc.subject.other	Tracking (position)	en
dc.subject.other	Video signal processing	en
dc.subject.other	Active contours	en
dc.subject.other	Cluttered sequences	en
dc.subject.other	Image sequences	en
dc.subject.other	Occlusion	en
dc.subject.other	Snakes	en
dc.subject.other	Tracking	en
dc.subject.other	Object recognition	en
dc.title	A snake model for object tracking in natural sequences	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.image.2003.07.002	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.image.2003.07.002	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	Tracking moving objects in video sequences is a task that emerges in various fields of study: video analysis, computer vision, biomedical systems, etc. In the last decade, special attention has been drawn to problems concerning tracking in real-world environments, where moving objects do not obey any afore-known constraints about their nature and motion or the scenes they are moving in. Apart from the existence of noise and environmental changes, many problems are also concerned, due to background texture, complicated object motion, and deformable and/or articulated objects, changing their shape while moving along time. Another phenomenon in natural sequences is the appearance of occlusions between different objects, whose handling requires motion information and, in some cases, additional constraints. In this work, we revisit one of the most known active contours, the Snakes, and we propose a motion-based utilization of it, aiming at successful handling of the previously mentioned problems. The use of the object motion history and first order statistical measurements of it, provide us with information for the extraction of uncertainty regions, a kind of shape prior knowledge w.r.t. the allowed object deformations. This constraining also makes the proposed method efficient, handling the trade-off between accuracy and computation complexity. The energy minimization is approximated by a force-based approach inside the extracted uncertainty regions, and the weights of the total snake energy function are automatically estimated as respective weights in the resulting evolution force. Finally, in order to handle background complexity and partial occlusion cases, we introduce two rules, according to which the moving object region is correctly separated from the background, whereas the occluded boundaries are estimated according to the object's expected shape. To verify the performance of the proposed method, some experimental results are included, concerning different cases of object tracking, indoors and outdoors, with rigid and deformable objects, noisy and textured backgrounds, as well as appearance of occlusions. (C) 2003 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Signal Processing: Image Communication	en
dc.identifier.doi	10.1016/j.image.2003.07.002	en
dc.identifier.isi	ISI:000189193300002	en
dc.identifier.volume	19	en
dc.identifier.issue	3	en
dc.identifier.spage	219	en
dc.identifier.epage	238	en