By Masao Sakauchi (auth.), Hiroshi Arisawa, Tiziana Catarci (eds.)

Video segmentation is the main primary procedure for applicable index­ ing and retrieval of video durations. mostly, video streams are composed 1 of pictures delimited by means of actual shot limitations. sizeable paintings has been performed on the right way to observe such shot barriers immediately (Arman et aI. , 1993) (Zhang et aI. , 1993) (Zhang et aI. , 1995) (Kobla et aI. , 1997). during the inte­ gration of applied sciences comparable to photograph processing, speech/character attractiveness and traditional language knowing, key phrases should be extracted and linked to those photographs for indexing (Wactlar et aI. , 1996). A unmarried shot, despite the fact that, not often contains sufficient quantity of knowledge to be significant on its own. Usu­ best friend, it's a semantically significant period that almost all clients have an interest in re­ trieving. often, such significant periods span numerous consecutive pictures. There rarely exists any effective and trustworthy method, both computerized or guide, to spot all semantically significant periods inside of a video circulation. Works by means of (Smith and Davenport, 1992) (Oomoto and Tanaka, 1993) (Weiss et aI. , 1995) (Hjelsvold et aI. , 1996) recommend manually defining all such inter­ vals within the database prematurely. although, even an hour lengthy video can have an indefinite variety of significant periods. additionally, video facts is multi­ interpretative. hence, given a question, what's a significant period to an annotator is probably not significant to the person who concerns the question. In perform, guide indexing of significant periods is labour extensive and inadequate.

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Additional info for Advances in Visual Information Management: Visual Database Systems. IFIP TC2 WG2.6 Fifth Working Conference on Visual Database Systems May 10–12, 2000, Fukuoka, Japan

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Since 1994, he is a professor of the Department of Computer and Systems Engineering and since 1997, he is a professor of Division of Media and Computer Science of Graduate School of Science and Technology at Kobe University. His research interests include object-oriented databases, video databases, historical database models, and hypermedia systems. Dr. Tanaka is a member of the ACM, IEEE Computer Society and the Information Processing Society of Japan. A New Algebraic Approach to Retrieve Meaningful Video Intervals 29 Appendix Theorem 1: For any intervals sets X and Y, the following expression holds.

His current research interests include high-speed networking and distributed multimedia. He was awarded the Prize of the Minister of the STA, the Achievement Prize of IEICE. He is a Technical Program Chairman of ICCC'99, member of IEICE and Fellow of IEEE. Shin'ichi Satoh is an associate professor at National Center for Science mformation Systems (NACSIS), Japan. He received his BE degree in 1987, his ME and PhD degrees in 1989 and 1992 from the University of Tokyo. His research interests include video analysis and multimedia database.

Then, there must be x E (X definition of interval glue (ffi), the following four possible cases can be considered on the basis of what values z takes for its starting and ending frame . I. z == z lf s{x ), f e{Y)] if f s{x) ::; fs{Y) and f e{Y) :0:: f e{x) Ee Ee II. z == z[Js{Y) , f e{x)] if f s{Y) ::; f s{x) and f e{x) :0:: f e{Y) III. z == zlfs{x), f e{x )] if f s{x) ::; f s{Y) and f e{x ) :0:: f e{Y) IV. z == zlfs{Y) , f e{Y)] if f s{Y) ::; f s{x) and f e{Y) :0:: f e{x) We will first consider Case I.

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