Object based coding of video sequences at low bit rates using adaptively trained neural networks

Doulamis, N; Doularnis, A; Kollias, S

dc.contributor.author	Doulamis, N	en
dc.contributor.author	Doularnis, A	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:48:11Z
dc.date.available	2014-03-01T01:48:11Z
dc.date.issued	1999	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25423
dc.subject	Probabilistic Model	en
dc.subject	Rate Control	en
dc.subject	Video Conferencing	en
dc.subject	Video Object Segmentation	en
dc.subject	Neural Network	en
dc.title	Object based coding of video sequences at low bit rates using adaptively trained neural networks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/ICECS.1999.813394	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICECS.1999.813394	en
heal.publicationDate	1999	en
heal.abstract	Unsupervised video object segmentation is proposed in this paper, using an adaptively trained neural network structure followed by a face and body detection scheme. The latter uses probabilistic modeling for applying the face and body detection task. The algorithm is incorporated along with a rate control mechanism, which allocates more bits to regions of importance, such as humans in video	en
dc.identifier.doi	10.1109/ICECS.1999.813394	en