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Proceedings Paper

Automatic home video abstraction using audio contents
Author(s): Ming Zhao; Chun Chen; Caifu Chen; JiaJun Bu
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Paper Abstract

With the increasing number of people who can afford to make videos to record their lives, home videos play more and more important role in people's lives. Video abstraction is an efficient way to help review such a huge amount of home videos. In this paper, an automatic home video abstraction method mainly using audio contents is presented. The audio contents are first segmented and classified as speech, music, silence and special sounds basing on audio short-time features and morphology. Then special sounds are further categorized as songs, laughter, applause, scream and others using Hidden Markov Model (HMM). After that, motion level and blur degree are acquired using the video contents. Finally, video segments containing special effects, such as speech, laughter, song, applause, scream, and specified motion level and blur degree, are extracted as the main parts of the abstract. The remaining parts of the abstract are generated using key frame information. The experimental results show that the proposed algorithm can extract desired parts ofhome video to generate satisfactory video abstracts

Paper Details

Date Published: 30 August 2002
PDF: 9 pages
Proc. SPIE 4925, Electronic Imaging and Multimedia Technology III, (30 August 2002); doi: 10.1117/12.481604
Show Author Affiliations
Ming Zhao, Zhejiang Univ. (China)
Chun Chen, Zhejiang Univ. (China)
Caifu Chen, Zhejiang Univ. (China)
JiaJun Bu, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 4925:
Electronic Imaging and Multimedia Technology III
LiWei Zhou; Chung-Sheng Li; Yoshiji Suzuki, Editor(s)

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