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A framework is proposed in this paper that is used to segment flow of densecrowds. The flow field that is generated by the movement in the crowd istreated just like an aperiodic dynamic system. On this flow field a grid ofparticles is put over for particle advection by the use of a numericalintegration scheme. Then flow maps are generated which associates the initialposition of the particles with final position. The gradient of the flow mapsgives the amount of divergence of the neighboring particles. For forwardintegration and analysis forward Finite time Lyapunov Exponent is calculatedand backward Finite time Lyapunov Exponent is also calculated it gives theLagrangian coherent structures of the flow in crowd. Lagrangian CoherentStructures basically divides the flow in crowd into regions and these regionshave different dynamics. These regions are then used to get the boundary in thedifferent flow segments by using water shed algorithm. The experiment isconducted on the crowd dataset of UCF (University of central Florida).

Flow Segmentation in Dense Crowds