Abstract
Human activity recognition is an important and challenging task for video content analysis and understanding. Individual activity recognition has been well studied recently. However, recognizing the activities of human group with more than three people having complex interactions is still a formidable challenge. In this paper, a novel human group activity recognition method is proposed to deal with complex situation where there are multiple sub-groups. To characterize the inherent interactions of intra-subgroups and inter-subgroups with the varying number of participants, this paper proposes three types of group-activity descriptor using motion trajectory and appearance information of people. Experimental results on a public human group activity dataset demonstrate effectiveness of the proposed method.
Original language | English |
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Title of host publication | Advances in Multimedia Information Processing – PCM 2015 - 16th Pacific-Rim Conference on Multimedia, Proceedings |
Editors | Yo-Sung Ho, Yong Man Ro, Junmo Kim, Fei Wu, Jitao Sang |
Publisher | Springer Verlag |
Pages | 161-169 |
Number of pages | 9 |
ISBN (Print) | 9783319240770 |
DOIs | |
Publication status | Published - 2015 |
Event | 16th Pacific-Rim Conference on Multimedia, PCM 2015 - Gwangju, Korea, Republic of Duration: 2015 Sept 16 → 2015 Sept 18 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9315 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Other
Other | 16th Pacific-Rim Conference on Multimedia, PCM 2015 |
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Country/Territory | Korea, Republic of |
City | Gwangju |
Period | 15/9/16 → 15/9/18 |
Bibliographical note
Funding Information:This research was supported by BK21 PLUS Program.
Publisher Copyright:
© Springer International Publishing Switzerland 2015.
Keywords
- Activity recognition
- Human group activity
- Video analytics
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science