Presentation 2007-02-22
Online Action Recognition with Structured Boosting
Yu NEJIGANE, Masamichi SHIMOSAKA, Taketoshi MORI, Tomomasa SATO,
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Abstract(in English) In this paper, we propose a robust online action recognition method based on boosted sequential classification. Our method utilizes boosting algorithm that is one of ensemble learning algorithms. This algorithm is also known as a feautre selector and has been utilized in the fields of image processing and natural language processing in recent years. Our method automatically and efficiently selects significant features for action recognition. Additionally, the method assumes interdependency between action labels based on Markov random fields. We evaluated our method to action recognition, such as walking and running, using motion capture data only with posture features. In the result, our method classified the actions more robustly than other methods that do not utilize interdependency between action labels.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Boosting / LogitBoost / Online Action Recognition / Motion Capture / Markov Random Fields
Paper # PRMU2006-216,HIP2006-109
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Conference Information
Committee PRMU
Conference Date 2007/2/15(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) Online Action Recognition with Structured Boosting
Sub Title (in English)
Keyword(1) Boosting
Keyword(2) LogitBoost
Keyword(3) Online Action Recognition
Keyword(4) Motion Capture
Keyword(5) Markov Random Fields
1st Author's Name Yu NEJIGANE
1st Author's Affiliation Graduate School of Information Science and Engineering, the University of Tokyo()
2nd Author's Name Masamichi SHIMOSAKA
2nd Author's Affiliation Graduate School of Information Science and Engineering, the University of Tokyo
3rd Author's Name Taketoshi MORI
3rd Author's Affiliation Graduate School of Information Science and Engineering, the University of Tokyo
4th Author's Name Tomomasa SATO
4th Author's Affiliation Graduate School of Information Science and Engineering, the University of Tokyo
Date 2007-02-22
Paper # PRMU2006-216,HIP2006-109
Volume (vol) vol.106
Number (no) 538
Page pp.pp.-
#Pages 6
Date of Issue