Real-time video surveillance on an embedded, programmable platform
Microprocessors & Microsystems
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Battery-powered wireless embedded smart cameras havelimited processing power, memory and energy. Since videoprocessing tasks consume significant amount of power,the problem of limited resources becomes even more pro-nounced, and necessitates designing light-weight algo-rithms suitable for embedded platforms. In this paper, wepresent a resource-efficient salient foreground detection andtracking algorithm. Contrary to traditional methods thatimplement foreground object detection and tracking inde-pendently and in a sequential manner, the proposed methoduses the feedback from the tracking stage in the foregroundobject detection. We compare the proposed method with asequential method on the microprocessor of an embeddedsmart camera, and present the savings in the processingtime and energy consumption and the gain in the lifetimeof a battery-powered camera for different scenarios. Thepresented method provides significant savings in terms ofthe processing time of a frame. We take advantage of thesesavings by sending the microprocessor to idle state at theend of processing a frame, and when the scene is empty.