Hidden Markov model parsing of video programs

@inproceedings{Wolf1997HiddenMM,
  title={Hidden Markov model parsing of video programs},
  author={Wayne H. Wolf},
  booktitle={ICASSP},
  year={1997}
}
This paper introduces statistical parsing of video programs using hidden Markov models (HMMs). The fundamental units of a video program are shots and transitions (fades, dissolves, etc.). Those units are in turn used to create more complex structures, such as scenes. Parsing a video allows us to recognize higher-level story abstractions—dialog sequences, transitional scenes, etc. These higher-level story elements can be used to create summarizations of the programs, to recognize the most… CONTINUE READING
Highly Cited
This paper has 53 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 33 extracted citations

Summarizing raw video material using Hidden Markov Models

2009 10th Workshop on Image Analysis for Multimedia Interactive Services • 2009
View 1 Excerpt

54 Citations

0510'97'02'08'14
Citations per Year
Semantic Scholar estimates that this publication has 54 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…