Presentation 2011-02-18
Human motion recognition in crowded surveillance video sequences based on key-point trajectories
Masaki TAKAHASHI, Mahito FUJII, Masahide NAEMURA, Shin'ichi SATOH,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) There is a need for systems that can automatically detect specific human motions in a surveillance video. However, almost all of the human motion recognition techniques proposed so far are for detecting relatively large motions within simple video sequences. To alleviate this shortcoming, we propose a method that can detect specific small motions within crowd sequences of real surveillance video. Our motion recognition method is based on the bag-of-features approach, and key-point trajectories are used as its features. The method extracts a fixed-length feature descriptor from a key-point trajectory and uses it for event classification. In addition, feature weights are calculated for reducing the interference from noise trajectories in the background regions. We confirmed the effectiveness of our proposed method in experiments comparing it with other techniques and in the TRECVID Surveillance Event Detection task.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Human behavior recognition / Surveillance / Bag-of-features
Paper # PRMU2010-225
Date of Issue

Conference Information
Committee PRMU
Conference Date 2011/2/10(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

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) Human motion recognition in crowded surveillance video sequences based on key-point trajectories
Sub Title (in English)
Keyword(1) Human behavior recognition
Keyword(2) Surveillance
Keyword(3) Bag-of-features
1st Author's Name Masaki TAKAHASHI
1st Author's Affiliation NHK Science and Technology Research Laboratories()
2nd Author's Name Mahito FUJII
2nd Author's Affiliation NHK Science and Technology Research Laboratories
3rd Author's Name Masahide NAEMURA
3rd Author's Affiliation NHK Science and Technology Research Laboratories
4th Author's Name Shin'ichi SATOH
4th Author's Affiliation National Institute of Informatics
Date 2011-02-18
Paper # PRMU2010-225
Volume (vol) vol.110
Number (no) 414
Page pp.pp.-
#Pages 6
Date of Issue