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We describe a lightweight method for counting and localizing people using camera sensor networks. The algorithm makes use of a motion histogram to detect people based on motion and size criteria. The motion histogram is an averaged shifted histogram that estimates the distribution of people in a room given the above-threshold pixels in a frame-differenced ldquomotionrdquo image. The algorithm provides good detection rates at low computational complexity. In this paper, we describe the details of our design and experimentally determine suitable parameters for the proposed histogram. The resulting histogram and counting algorithm are implemented and tested on a network of iMote2 sensor nodes. Our implementation on sensor nodes uses a custom sensor board with a commercial off-the-shelf camera, but the motion histogram is designed to easily adapt to ultralow-power address-event motion imagers.