An Ultra-Low-Power Contrast-Based Camera Node and its Application as a People Counter

We describe the implementation in a self-standing system of a novel contrast-based binary CMOS imaging sensor. This sensor is characterized by very low power consumption and wide dynamic range, which makes it attractive for wireless camera network applications. In our implementation, the sensor is interfaced with a Flash-based FPGA processor, which handles data readout and image processing. This self-standing camera node is configured as a system for counting persons walking through a corridor. Simple features are extracted from each image in a video stream at 30 fps. A classifier is designed based on the temporal evolution of these features, which is modeled as a Markov chain. The video stream is then segmented into intervals corresponding to individual persons crossing through the field of view. Experimental results are shown in cross-validated tests over real sequences acquired by the camera.