Event detection and recognition using histogram of oriented gradients and hidden markov models

Authors:
Chun-hao Wang;Yongjin Wang;Ling Guan
Affiliations:
Ryerson University, Electrical and Computer Engineering, Toronto, Ontario, Canada;Ryerson University, Electrical and Computer Engineering, Toronto, Ontario, Canada;Ryerson University, Electrical and Computer Engineering, Toronto, Ontario, Canada
Venue:
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Year:
2011

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Abstract

This paper presents an approach for object detection and event recognition in video surveillance scenarios. The proposed system utilizes a Histogram of Oriented Gradients (HOG) method for object detection, and a Hidden Markov Model (HMM) for capturing the temporal structure of the features. Decision making is based on the understanding of objects motion trajectory and the relationships between objects' movement and events. The proposed method is applied to recognize events from the public PETS and i-LIDS datasets, which include vehicle events such as U-turns and illegal parking, as well as abandoned luggage recognition established by set of rules. The effectiveness of the proposed solution is demonstrated through extensive experimentation.