Energy-aware objects abandon/removal detection

A major issue for video surveillance embedded systems is the need to continuously perform a number of highly demanding operations even when the analyzed scene does not show peculiar or interesting features, so that power consumption is a critical issue. In this paper we present a low-power multimodal embedded video surveillance system aimed at detecting objects abandoned/removed in/from a static monitored scene. Energy-awareness is achieved by means of an efficient and scalable objects abandon/removal detection algorithm, a Linux governor that controls CPU frequency and operating mode so as to establish an optimal trade-off between fulfilling the application efficiency-accuracy requirements and maximizing battery life and, finally, a pyroelectric infrared sensor that allows to wake up the CPU only when video processing is actually needed.