Event Detection in Crowds of People by Integrating Chaos and Lagrangian Particle Dynamics
TL;DRAbstract
This paper proposes a system for automatic video analysis to detect events in video sequences with crowds of people. In detail, the proposed system consists of three subsystems: 1) the first identifies the motion areas, resorting to chaos theory using joint histogram between consecutive frames, 2) the second one creates a flow motion map that describes the behavior of motion pixels by using Lagrangian Particle Dynamics Theory and, 3) the last one uses self organizing maps (SOM) for segmenting the flow motion map in order to detect events.
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This paper proposes a system for automatic video analysis to detect events in video sequences with crowds of people. In detail, the proposed system consists of three subsystems: 1) the first identifies the motion areas, resorting to chaos theory using joint histogram between consecutive frames, 2) the second one creates a flow motion map that describes the behavior of motion pixels by using Lagrangian Particle Dynamics Theory and, 3) the last one uses self organizing maps (SOM) for segmenting the flow motion map in order to detect events.
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