A Novel Approach to Video Database Indexing via Semantic Classification

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The goal of this research project is to develop a novel framework to support more effective and secure content-based video access over large-scale database. Specifically, the framework includes: (a) a hierarchical video database management and indexing structure to define the contextual and logical relationships among the related visual concepts and thus facilitate more efficient video access; (b) a probabilistic semantic video classifier to bridge the semantic gap between the low-level visual features and the high-level visual concepts; (c) a hierarchical visual summarization and presentation technique to enable fast video browsing over IP networks; (d) a multi-level video database access control scheme to serve different classes of users and maintain the video data integrity and security. A wide range of potential applications could benefit from this research, such as education and distance learning, health care and telemedicine, digital library, national security and defense, network-based media, and entertainment