Abstract
In this paper, we address the problem of recognizing group activities that include interactions between human objects based on their motion trajectory analysis. In order to resolve the complexity and ambiguity problems caused by a large number of human objects, we propose a Group Interaction Zone (GIZ) to detect meaningful groups in a scene so as to be robust against noisy information. Two novel features, Group Interaction Energy feature and Attraction and Repulsion Features, are proposed to better describe group activities within a GIZ. We demonstrate the effectiveness of our method with other methods on the public BEHAVE dataset.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - International Conference on Pattern Recognition |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3517-3521 |
| Number of pages | 5 |
| ISBN (Print) | 9781479952083 |
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
| Event | 22nd International Conference on Pattern Recognition, ICPR 2014 - Stockholm, Sweden Duration: 2014 Aug 24 → 2014 Aug 28 |
Other
| Other | 22nd International Conference on Pattern Recognition, ICPR 2014 |
|---|---|
| Country | Sweden |
| City | Stockholm |
| Period | 14/8/24 → 14/8/28 |
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ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
Cite this
Group activity recognition with group interaction zone. / Kim, Young Ji; Cho, Nam Gyu; Lee, Seong Whan.
Proceedings - International Conference on Pattern Recognition. Institute of Electrical and Electronics Engineers Inc., 2014. p. 3517-3521 6977317.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Group activity recognition with group interaction zone
AU - Kim, Young Ji
AU - Cho, Nam Gyu
AU - Lee, Seong Whan
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In this paper, we address the problem of recognizing group activities that include interactions between human objects based on their motion trajectory analysis. In order to resolve the complexity and ambiguity problems caused by a large number of human objects, we propose a Group Interaction Zone (GIZ) to detect meaningful groups in a scene so as to be robust against noisy information. Two novel features, Group Interaction Energy feature and Attraction and Repulsion Features, are proposed to better describe group activities within a GIZ. We demonstrate the effectiveness of our method with other methods on the public BEHAVE dataset.
AB - In this paper, we address the problem of recognizing group activities that include interactions between human objects based on their motion trajectory analysis. In order to resolve the complexity and ambiguity problems caused by a large number of human objects, we propose a Group Interaction Zone (GIZ) to detect meaningful groups in a scene so as to be robust against noisy information. Two novel features, Group Interaction Energy feature and Attraction and Repulsion Features, are proposed to better describe group activities within a GIZ. We demonstrate the effectiveness of our method with other methods on the public BEHAVE dataset.
UR - http://www.scopus.com/inward/record.url?scp=84919941195&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84919941195&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2014.605
DO - 10.1109/ICPR.2014.605
M3 - Conference contribution
AN - SCOPUS:84919941195
SN - 9781479952083
SP - 3517
EP - 3521
BT - Proceedings - International Conference on Pattern Recognition
PB - Institute of Electrical and Electronics Engineers Inc.
ER -