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Surveillance typically involves monitoring humans, buildings, and other mobile objects to detect abnormal behavior; primarily to sense and detect any anomalies in real time. Conventionally this has been done manually, but with a growing demand for day-to-day surveillance and the need for intense monitoring; decision support has proven to improve the overall system performance. Decision support also...
Typically sensor networks rely on centralized information processing where the sensed information is relayed to a network hub. The network then processes the information and adjusts the network according to the perceived state of its environment. In this paper we propose a novel collective decision making approach. Instead of relaying all the sensor information to a central location, the nodes process...
This paper presents a graphical model approach that fuses thermal infrared (IR) and visible spectrum video for human tracking. The proposed model uses unobserved variables to describe the data in terms of the process that generates them. It is thus able to capture and exploit the statistical structure of the IR and the visible data separately, as well as their mutual dependencies. Model parameters...
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