A new content-based access method for video databases

Abstract

This paper presents a novel video data model and a nested annotation language for describing complex information of video data. In contrast to conventional approaches, the proposed model classifies different video materials of interest to users into different representation frameworks according to their individual properties. It makes the model flexible and capable of sharing video materials. The nested annotation language effectively describes scenarios in video data and can be effectively analysed. With the assistance of domain knowledge and index organizations this investigaton also develops algorithms to effectively process five types of familiar video queries: semantic query, temporal quaery, similar query, fuzzy query and hybrid query. In addition, a SQL-like query language for video content retrival is provided. Experimental results indicate that combining the concepts of Bayesian networks and inheritance of attributes by context significantly improves the content based retrieval of video data. Moreover a prototype system based on proposed model has been implemented. (C) 1999 Published by Elsevier Science Inc. All rights reserved.