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Intrusion Detection and Cooperative Tracking Using PTZ Network Thermal Imagers
Author(s) -
Zhenghao Li,
Junying Yang,
Peng Han,
Ran Yang,
Zhi Chai
Publication year - 2015
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2015/130103
Subject(s) - computer science , intrusion detection system , tracking (education) , frame (networking) , computer vision , artificial intelligence , offset (computer science) , frame rate , field of view , intrusion , zoom , key (lock) , matching (statistics) , real time computing , computer network , computer security , psychology , pedagogy , statistics , mathematics , geochemistry , lens (geology) , petroleum engineering , engineering , programming language , geology
Nowadays more and more network thermal imaging cameras are working over distributed networks, offering the capability of online remote intelligent video surveillance. In this paper, we propose an original intrusion detection and cooperative tracking approach applied for PTZ (Pan/Tilt/Zoom) network thermal imagers. It consists of three modules. The key module is the real-time FOV (Field of View) matching module, which is realized in a parallel way. The intrusion detection module first eliminates the offset between current frame and prior frame through FOV matching and then handles intrusion detection by motion detection in the preset surveillance zone. The cooperative tracking module shifts the priority of tracking by imager pose estimation, which is also based on FOV matching, avoiding transferring the local features from one imager to another. Experiments are conducted to demonstrate that the proposed approach is of high accuracy for intrusion detection and cooperative tracking and keeps the frame rate over 20 fps.

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