In this paper we propose a motion-based people counting al- gorithm 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 occlu- sions 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 abil- ity to work in different types of scenarios. We report results on both benchmark and acquired in-house datasets of differ- ent degrees of complexity, showing how our solution achieves comparable or superior performances with respect to state-of- art methods, while providing real-time performances.
Precise people counting in real time
ZINI, LUCA;NOCETI, NICOLETTA;ODONE, FRANCESCA
2013-01-01
Abstract
In this paper we propose a motion-based people counting al- gorithm 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 occlu- sions 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 abil- ity to work in different types of scenarios. We report results on both benchmark and acquired in-house datasets of differ- ent degrees of complexity, showing how our solution achieves comparable or superior performances with respect to state-of- art methods, while providing real-time performances.
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