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Journal of Electronic Imaging

Recognizing suspicious activities in infrared imagery using appearance-based features and the theory of hidden conditional random fields for outdoor perimeter surveillance
Author(s): Savvas Rogotis; Christos Palaskas; Dimosthenis Ioannidis; Dimitrios Tzovaras; Spiros Likothanassis
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Paper 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.

Paper Details

Date Published: 22 December 2015
PDF: 10 pages
J. Electron. Imaging. 24(6) 061111 doi: 10.1117/1.JEI.24.6.061111
Published in: Journal of Electronic Imaging Volume 24, Issue 6
Show Author Affiliations
Savvas Rogotis, Ctr. for Research and Technology Hellas (Greece)
Christos Palaskas, Ctr. for Research and Technology Hellas (Greece)
Dimosthenis Ioannidis, Ctr. for Research and Technology Hellas (Greece)
Univ. of Patras (Greece)
Dimitrios Tzovaras, Ctr. for Research and Technology Hellas (Greece)
Spiros Likothanassis, Univ. of Patras (Greece)


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