An accurate estimation of the number of people entering / leaving a controlled area is an interesting capability for automatic surveillance systems. Potential applications where this technology can be applied include those related to security, safety, energy saving or fraud control. In this paper we present a novel configuration of a multi-sensor system combining both visual and range data specially suited for troublesome scenarios such as public transportation. The approach applies probabilistic estimation filters on raw sensor data to create intermediate level hypothesis that are later fused using a certainty-based integration stage. Promising results have been obtained in several tests performed on a realistic test bed scenario under variable lightning conditions.
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