DocumentCode :
639503
Title :
Multi-agent Event Detection: Localization and Role Assignment
Author :
Kwak, Sangshin ; Bohyung Han ; Joon Hee Han
Author_Institution :
Dept. of Comput. Sci. & Eng., POSTECH, Pohang, South Korea
fYear :
2013
fDate :
23-28 June 2013
Firstpage :
2682
Lastpage :
2689
Abstract :
We present a joint estimation technique of event localization and role assignment when the target video event is described by a scenario. Specifically, to detect multi-agent events from video, our algorithm identifies agents involved in an event and assigns roles to the participating agents. Instead of iterating through all possible agent-role combinations, we formulate the joint optimization problem as two efficient sub problems-quadratic programming for role assignment followed by linear programming for event localization. Additionally, we reduce the computational complexity significantly by applying role-specific event detectors to each agent independently. We test the performance of our algorithm in natural videos, which contain multiple target events and nonparticipating agents.
Keywords :
computational complexity; image recognition; linear programming; multi-agent systems; quadratic programming; video signal processing; computational complexity; event localization; joint optimization problem; linear programming; multiagent event detection; multiple target events; natural videos; nonparticipating agents; quadratic programming; role assignment; role-specific event detectors; Estimation; Event detection; Hidden Markov models; Joints; Linear programming; Optimization; Vectors; activity detection; video event detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location :
Portland, OR
ISSN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2013.346
Filename :
6619190
Link To Document :
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