Special Section on Quality Control by Artificial Vision: Nonconventional Imaging Systems

Recognizing suspicious activities in infrared imagery using appearance-based features and the theory of hidden conditional random fields for outdoor perimeter surveillance

[+] Author Affiliations
Savvas Rogotis, Christos Palaskas, Dimitrios Tzovaras

Information Technologies Institute, Centre for Research and Technology Hellas, 6th km Harilaou-Thermi, P.O. Box 60361, Thessaloniki 57001, Greece

Dimosthenis Ioannidis

Information Technologies Institute, Centre for Research and Technology Hellas, 6th km Harilaou-Thermi, P.O. Box 60361, Thessaloniki 57001, Greece

University of Patras, Pattern Recognition Laboratory—Computer Engineering and Informatics, University of Patras Campus, Building B, Rio 26500, Patras, Greece

Spiros Likothanassis

University of Patras, Pattern Recognition Laboratory—Computer Engineering and Informatics, University of Patras Campus, Building B, Rio 26500, Patras, Greece

J. Electron. Imaging. 24(6), 061111 (Dec 22, 2015). doi:10.1117/1.JEI.24.6.061111
History: Received June 30, 2015; Accepted November 16, 2015
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Abstract.  This work aims to present an extended framework for automatically recognizing suspicious activities in outdoor perimeter surveilling systems based on infrared video processing. By combining size-, speed-, and appearance-based features, like the local phase quantization and the histograms of oriented gradients, actions of small duration are recognized and used as input, along with spatial information, for modeling target activities using the theory of hidden conditional random fields (HCRFs). HCRFs are used to classify an observation sequence into the most appropriate activity label class, thus discriminating high-risk activities like trespassing from zero risk activities, such as loitering outside the perimeter. The effectiveness of this approach is demonstrated with experimental results in various scenarios that represent suspicious activities in perimeter surveillance systems.

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Citation

Savvas Rogotis ; Christos Palaskas ; Dimosthenis Ioannidis ; Dimitrios Tzovaras and Spiros Likothanassis
"Recognizing suspicious activities in infrared imagery using appearance-based features and the theory of hidden conditional random fields for outdoor perimeter surveillance", J. Electron. Imaging. 24(6), 061111 (Dec 22, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.6.061111


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