Structural Analysis Of Videos With Hidden Markov Models And Dynamic Programming


A method analyzes a high-level syntax and structure of a continuous compressed video according to a plurality of states. First, a set of hidden Markov models for each of the states is trained with a training video segmented into known states. Then, a set of domain specific features are extracted from a fixed-length sliding window of the continuous compressed video, and a set of maximum likelihoods is determined for each set of domain specific features using the sets of trained hidden Markov models. Finally, dynamic programming is applied to each set of maximum likelihoods to determine a specific state for each fixed-length sliding window of frames of the compressed video.

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Document History
  • Publication: Mar 8, 2005
  • Application: Dec 5, 2001
    US US 562301 A
  • Priority: Dec 5, 2001
    US US 562301 A

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