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We propose two approaches for semantic indexing of audio-visual documents, based on bottom-up and top-down strategies. We base the first approach on a finite-state machine using low-level motion indices extracted from an MPEG compressed bitstream. The second approach innovatively performs semantic indexing through Hidden Markov Models.
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Leonardi et al. (2002) studied this question.
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