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Proceedings Paper

Video segmentation by hidden Markov model using multimodal MPEG-7 descriptors
Author(s): Tae Meon Bae; Sung Ho Jin; Jin Ho Choo; Mansoo Park; Yong Man Ro; Hoi-Rin Kim; Kyeongok Kang
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Paper 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.

Paper Details

Date Published: 15 December 2003
PDF: 10 pages
Proc. SPIE 5304, Internet Imaging V, (15 December 2003); doi: 10.1117/12.526385
Show Author Affiliations
Tae Meon Bae, Information and Communications Univ. (South Korea)
Sung Ho Jin, Information and Communications Univ. (South Korea)
Jin Ho Choo, Information and Communications Univ. (South Korea)
Mansoo Park, Information and Communications Univ. (South Korea)
Yong Man Ro, Information and Communications Univ. (South Korea)
Hoi-Rin Kim, Information and Communications Univ. (South Korea)
Kyeongok Kang, Electronics and Telecommunications Research Institute (South Korea)


Published in SPIE Proceedings Vol. 5304:
Internet Imaging V
Simone Santini; Raimondo Schettini, Editor(s)

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