Trajectories clustering in ICA space: an application to automatic counting of pedestrians in video sequences

In this paper we propose a method for the automatic counting of pedestrians in video sequences for (automatic) video surveillance applications. We analyse the trajectory data set provided by a detection/tracking system. When using classical target detection and tracking systems, it is well known that the number of detected targets is overestimated/ underestimated. A better representation for the trajectories is given in the ICA (Independent Component Analysis) transformed domain and clustering techniques are applied to the ICA-transformed data in order to provide a better estimation of the actual number of pedestrians which are present on the scene.


Published in:
Advanced Concepts for Intelligent Vision Systems, ACIVS 2004, Brussels, Belgium
Year:
2004
Publisher:
IEEE
Keywords:
Laboratories:




 Record created 2006-06-14, last modified 2018-03-17

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