Video segmentation by hidden Markov model using multimodal MPEG-7 descriptors

Tae Meon Bae; Sung Ho Jin; Jin Ho Choo; Mansoo Park; Yong Man Ro; Hoi-Rin Kim; Kyeongok Kang

doi:10.1117/12.526385

15 December 2003 Video segmentation by hidden Markov model using multimodal MPEG-7 descriptors

Tae Meon Bae, Sung Ho Jin, Jin Ho Choo, Mansoo Park, Yong Man Ro, Hoi-Rin Kim, Kyeongok Kang

Proceedings Volume 5304, Internet Imaging V; (2003) https://doi.org/10.1117/12.526385
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

Abstract

We propose a robust video segmentation algorithm for video summary. Exact shot boundary detection and segmentation of video into meaningful scenes are important parts for the automatic video summary. In this paper, we present a shot boundary detection using audio and visual features defined in the MPEG-7 which provides software standard for multimedia description. By using Hidden Markov Model classifier based on statistics of the audio and visual features, exact shot boundary is detected and further over-segmentation could be reduced, which is a common problem in automatic video segmentation.

Citation Download Citation

Tae Meon Bae, Sung Ho Jin, Jin Ho Choo, Mansoo Park, Yong Man Ro, Hoi-Rin Kim, and Kyeongok Kang "Video segmentation by hidden Markov model using multimodal MPEG-7 descriptors", Proc. SPIE 5304, Internet Imaging V, (15 December 2003); https://doi.org/10.1117/12.526385

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