Video representation and retrieval using spatio-temporal descriptors and region relations

Chatzis, S; Doulamis, A; Kosmopoulos, D; Varvarigou, T

dc.contributor.author	Chatzis, S	en
dc.contributor.author	Doulamis, A	en
dc.contributor.author	Kosmopoulos, D	en
dc.contributor.author	Varvarigou, T	en
dc.date.accessioned	2014-03-01T02:44:22Z
dc.date.available	2014-03-01T02:44:22Z
dc.date.issued	2006	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31774
dc.subject	ARVQ	en
dc.subject	Graph Matching	en
dc.subject	Machine Learning	en
dc.subject	Region	en
dc.subject	Spatio-Temporal	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	ARVQ	en
dc.subject.other	Graph Matching	en
dc.subject.other	Spatio Temporal	en
dc.subject.other	Algorithms	en
dc.subject.other	Graph theory	en
dc.subject.other	Learning systems	en
dc.subject.other	Problem solving	en
dc.subject.other	Video cameras	en
dc.title	Video representation and retrieval using spatio-temporal descriptors and region relations	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/11840930_10	en
heal.identifier.secondary	http://dx.doi.org/10.1007/11840930_10	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	This paper describes a novel methodology for video summarization and representation. The video shots are processed in space-time as 3D volumes of pixels. Pixel regions with consistent color and motion properties are extracted from these 3D volumes by a space-time segmentation technique based on a novel machine learning algorithm. Each region is then described by a high-dimensional point whose components represent the average position, motion velocity and color of the region. Subsequently, the spatio-temporal relations of the regions are deduced and a concise, graph-based description of them is generated. This graph-based description of the video shot's content, along with the region centroids, comprises a concise yet powerful description of the video-shot and is used for retrieval applications. The retrieval problem is formulated as an inexact graph matching problem between the data video shots and the query input which is also a video segment. Experimental results on action recognition and video retrieval are illustrated and discussed. © Springer-Verlag Berlin Heidelberg 2006.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.doi	10.1007/11840930_10	en
dc.identifier.isi	ISI:000241475200010	en
dc.identifier.volume	4132 LNCS - II	en
dc.identifier.spage	94	en
dc.identifier.epage	103	en