Refereed full papers (journals, book chapters, international conferences)

2004

@inproceedings{MeS2004,
	vgclass =	{refpap},
	author =	{Vasileios Mezaris1 and Michael G. Strintzis},
	title =	{Object Segmentation and Ontologies for MPEG-2 Video
	Indexing and Retrieval},
	booktitle =	{Proceedings of the Third International Conference on Image
	and Video Retrieval (CIVR 2004)},
	address =	{Dublin, Ireland},
	number =	{3115},
	series =	{Lecture Notes in Computer Science},
	pages =	{573--581},
	publisher =	{Springer-Verlag},
	month =	{July~21--23},
	year =	{2004},
	url =	{http://www.springerlink.com/link.asp?id=34gk3w69wxh39yaq},
	abstract =	{A novel approach to object-based video indexing and
	retrieval is presented, employing an object segmentation algorithm for
	the real-time, unsupervised segmentation of compressed image sequences
	and simple ontologies for retrieval. The segmentation algorithm uses
	motion information directly extracted from the MPEG-2 compressed stream
	to create meaningful foreground spatiotemporal objects, while
	background segmentation is additionally performed using color
	information. For the resulting objects, MPEG-7 compliant low-level
	indexing descriptors are extracted and are automatically mapped to
	appropriate intermediate-level descriptors forming a simple vocabulary
	termed object ontology. This, combined with a relevance feedback
	mechanism, allows the qualitative definition of the high-level concepts
	the user queries for (semantic objects, each represented by a keyword)
	and the retrieval of relevant video segments. Experimental results
	demonstrate the effectiveness of the proposed approach.},
}