A people counting system based on head-shoulder detection and tracking in surveillance video

Real-time people flow information is very useful for security application as well as people management. This paper presents a counting system which consists of four modules: foreground extraction, head-shoulder component detection, tracking and trajectory analysis. Firstly, in order to reduce comput...

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Veröffentlicht in:2010 International Conference On Computer Design and Applications Jg. 1; S. V1-394 - V1-398
Hauptverfasser: Huazhong Xu, Pei Lv, Lei Meng
Format: Tagungsbericht
Sprache:Englisch
Japanisch
Veröffentlicht: IEEE 01.06.2010
Schlagworte:
Application software
background substraction
Cameras
Computer vision
Data mining
Gaussian processes
HOG-features
Humans
Lighting
Motion detection
pedestrain detection
people counting
Trajectory
trajectory analysis
Video surveillance
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Zusammenfassung:Real-time people flow information is very useful for security application as well as people management. This paper presents a counting system which consists of four modules: foreground extraction, head-shoulder component detection, tracking and trajectory analysis. Firstly, in order to reduce computation costs and cope with various complex surveillance situations for foreground extraction, an adaptive components number selection strategy for mixture of Gaussians model is proposed. Secondly, pedestrians are detected by their head-shoulders, because this part is less varied and less likely occluded from a downward-slope view. Thirdly, each pedestrian is tracked through consecutive frames using the Kalman filter techniques and cost function. Finally, the resulting trajectories are analyzed to count people entering or leaving the scene. Experiment results indicate that our method can be applied in actual application.
DOI:10.1109/ICCDA.2010.5540833