An efficient and robust system for multi-person event detection in real world indoor surveillance scenes

Xu, Jingxin, Denman, Simon, Sridharan, Sridha, & Fookes, Clinton (2014) An efficient and robust system for multi-person event detection in real world indoor surveillance scenes. IEEE Transactions on Circuits and Systems for Video Technology, 25(6), pp. 1063-1076.

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Abstract

Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

Impact and interest:

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ID Code: 77989
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Event Detection, Video Surveillance, TRECVid SED, Topic Model, MPEG
DOI: 10.1109/TCSVT.2014.2367352
ISSN: 1051-8215
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Circuits and Systems (090601)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Funding:
Copyright Owner: Copyright 2014 IEEE
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Deposited On: 23 Oct 2014 01:11
Last Modified: 24 Jun 2015 01:56

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