Gathering Event Detection by Stereo Vision

This paper proposes a method for pedestrian gathering detection in real cluttered scenario by stereo vision. Firstly, foreground is converted into 3D cloud points and extracted by spatial confinement with more insensitivity to illumination change. Instead of detecting stationary people in camera view, they are localized in plan view maps which is more resistant to inter person occlusion and people number is directly estimated in multiple plan view statistical maps based on more physically inspired features by regression. In addition, it exhibits superior extensibility to multiple binocular camera system for wider surveillance coverage and higher detection accuracy through fusion. Finally, we contributed the first abnormal dataset with depth information and experimental results on it validate its effectiveness.

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