Video object segmentation and tracking in stereo sequences using adaptable neural networks

Doulamis, N; Doulamis, A

dc.contributor.author	Doulamis, N	en
dc.contributor.author	Doulamis, A	en
dc.date.accessioned	2014-03-01T02:42:21Z
dc.date.available	2014-03-01T02:42:21Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30969
dc.subject	Adaptive Neural Network	en
dc.subject	Object Extraction	en
dc.subject	Training Algorithm	en
dc.subject	Video Object Segmentation	en
dc.subject.other	Algorithms	en
dc.subject.other	Computer architecture	en
dc.subject.other	Decision theory	en
dc.subject.other	Feature extraction	en
dc.subject.other	Neural networks	en
dc.subject.other	Theorem proving	en
dc.subject.other	Decision mechanism	en
dc.subject.other	Stereo sequences	en
dc.subject.other	Image segmentation	en
dc.title	Video object segmentation and tracking in stereo sequences using adaptable neural networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2003.1246920	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2003.1246920	en
heal.publicationDate	2003	en
heal.abstract	In this paper, an adaptive neural network architecture is proposed for efficient video object segmentation and tracking of stereoscopic sequences. The scheme includes (a) a retraining algorithm for adapting network weights to current conditions, (b) a semantically meaningful object extraction module for creating a retraining set and (c) a decision mechanism, which detects the time instances that a new network retraining is required. The retraining algorithm optimally adapts network weights by exploiting information of the current condition with a minimal deviation of the network weights. Description of the current conditions is provided by a segmentation fusion scheme, which appropriately combines color and depth information.	en
heal.journalName	IEEE International Conference on Image Processing	en
dc.identifier.doi	10.1109/ICIP.2003.1246920	en
dc.identifier.volume	1	en
dc.identifier.spage	149	en
dc.identifier.epage	152	en