A utility framework for the automatic generation of audio-visual skims
Proceedings of the tenth ACM international conference on Multimedia
Concept-oriented indexing of video databases: toward semantic sensitive retrieval and browsing
IEEE Transactions on Image Processing
Large-scale video retrieval via semantic classification
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
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Effective video skimming requires a good understanding of the semantics of video contents. However, more existing systems for content-based video retrieval (CBVR) can only support low-level video analysis, but they have limited effectiveness on achieving semantic-sensitive video understanding. In this paper, we have developed a novel framework to achieve concept-oriented video skimming and it consists of three parts: (a) using salient objects for semantic-sensitive video content representation; (b) using finite mixture models for semantic video concept modeling and classification; (c) enabling concept-oriented video skimming via semantic video classification.