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This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics...
In this paper, we designed a simple and fast visual surveillance system to track human position and to determine if any abnormal behavior like wall climbing and falling happened. By taking both time and background difference into considerations, illumination effects could be greatly reduced while calculating motion masks. Refinements including holes filling, shadow removal, and noise reduction are...
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