Precise people counting in real time

In this paper we propose a motion-based people counting algorithm that relies on a weak camera calibration and produces a smooth estimate of the number of people in the scene. The method performs an analysis of the severity of possible occlusions and the integration of instantaneous observations over time. The key features of the algorithm are a simple pipeline, a small computational cost, the use of a model-free approach that does not need complex training procedures and its ability to work in different types of scenarios. We report results on both benchmark and acquired in-house datasets of different degrees of complexity, showing how our solution achieves comparable or superior performances with respect to state-of-art methods, while providing real-time performances.