This paper presents an application for counting people
through a single fixed camera. This system performs the count
distinction between input and output of people moving through
the supervised area. The counter requires two steps: detection and
tracking. The detection is based on finding people’s heads through
preprocessed image correlation with several circular patterns.
Tracking is made through the application of a Kalman filter to
determine the trajectory of the candidates. Finally, the system
updates the counters based on the direction of the trajectories.
Different tests using a set of real video sequences taken from
different indoor areas give results ranging between 87% and 98%
accuracies depending on the volume of flow of people crossing the
counting zone. Problematic situations, such as occlusions, people
grouped in different ways, scene luminance changes, etc., were
used to validate the performance of the system.
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