Affective content detection using HMMs

This paper discusses a new technique for detecting affective events using Hidden Markov Models(HMM). To map low level features of video data to high level emotional events, we perform empirical study on the relationship between emotional events and low-level features. After that, we compute simple low-level features that represent emotional characteristics and construct a token or observation vector by combining low level features. The observation vector sequence is tested to detect emotional events through HMMs. We create two HMM topologies and test both topologies. The affective events are detected from our proposed models with good accuracy.

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