Paper Info
Title
Group Activity Recognition with Group Interaction Zone
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.
Year
DOI
Venue
2014
10.1109/ICPR.2014.605
ICPR
Keywords
Field
DocType
group interaction zone,attraction-and-repulsion feature,public behave dataset,human computer interaction,ambiguity problem,giz,group interaction energy feature,motion trajectory analysis,complexity problem,noisy information,feature extraction,object detection,object recognition,computer vision,group activity recognition problem,group detection,human-computer interaction,video surveillance,image motion analysis
Computer vision,Pattern recognition,Feature (computer vision),Computer science,Group activity recognition,Group interaction,Artificial intelligence,Attraction,Trajectory analysis,Ambiguity
Conference
ISSN
Citations 
PageRank 
1051-4651
5
0.38
References 
Authors
10
3
Name
Order
Citations
PageRank
Ji Young Kim1389.66
Nam-Gyu Cho21508.31
Seong-Whan Lee33756343.90