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