Presentation 2007-12-13
Tagging Video Contents Based on Interest Estimation from Facial Expression
Masanori MIYAHARA, Masaki AOKI, Tetsuya TAKIGUCHI, Yasuo ARIKI,
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Abstract(in English) Recently, there are so many videos available for people to choose to watch. To solve this problem, we propose a tagging system for video content based on facial expression that can be used for video content recommendations. Viewer's face captured by a camera is extracted by Elastic Bunch Graph Matching, and Interest class is estimated by Support Vector Machines. The interest classes are Neutral, Positive, Negative and Rejective. They are recorded as "interest tags" in synchronization with video content. Experimental results achieved an averaged recall rate of 87.61%, and averaged precision rate of 88.03%.
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Keyword(in English) Tagging video contents / Facial expression / Elastic Bunch Graph Matching / Support Vector Machines
Paper # PRMU2007-137
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Committee PRMU
Conference Date 2007/12/6(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Tagging Video Contents Based on Interest Estimation from Facial Expression
Sub Title (in English)
Keyword(1) Tagging video contents
Keyword(2) Facial expression
Keyword(3) Elastic Bunch Graph Matching
Keyword(4) Support Vector Machines
1st Author's Name Masanori MIYAHARA
1st Author's Affiliation Graduate School of Engineering, Kobe University()
2nd Author's Name Masaki AOKI
2nd Author's Affiliation Graduate School of Engineering, Kobe University
3rd Author's Name Tetsuya TAKIGUCHI
3rd Author's Affiliation Organization of Advanced Science and Technology, Kobe University
4th Author's Name Yasuo ARIKI
4th Author's Affiliation Organization of Advanced Science and Technology, Kobe University
Date 2007-12-13
Paper # PRMU2007-137
Volume (vol) vol.107
Number (no) 384
Page pp.pp.-
#Pages 6
Date of Issue