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This paper presents a lightweight method for localizing and counting people in indoor spaces using motion and size criteria. A histogram designed to filter moving objects within a specified size range, can operate directly on frame difference output to localize human-sized moving entities in the field of view of each camera node. Our method targets a custom, ultra-low power imager architecture operating on address-event representation, aiming to implement the proposed algorithm on silicon. 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 set of iMote2 camera sensor nodes deployed in our lab.