Abstract
Most existing systems for content-based video retrieval (CBVR) are now amenable to support automatic low-level video content analysis and feature extraction, but they have limited effectiveness from a user's perspective. To support semantic video retrieval via keywords, we have proposed a novel framework by incorporating the concept ontology to enable more effective modeling and representation of semantic video concepts. Specifically, this novel framework includes: (a) Using the salient objects to achieve a middle-level understanding of the semantics of video contents; (b) Building a domain dependent concept ontology to enable multi-level modeling and representation of semantic video concepts; (c) Developing a multi-task boosting technique to achieve hierarchical video classifier training for automatic multi-level video annotation. The experimental results in a certain domain of medical education videos are also provided.
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