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Abnormal prediction of dense crowd videos by a purpose-driven lattice Boltzmann model

Xue Y., Liu P., Tao Y., Tang X.

International Journal of Applied Mathematics and Computer Science

2017

Vol. 27, no. 1

181--194

In the field of intelligent crowd video analysis, the prediction of abnormal events in dense crowds is a well-known and challenging problem. By analysing crowd particle collisions and characteristics of individuals in a crowd to follow the general trend of motion, a purpose-driven lattice Boltzmann model (LBM) is proposed. The collision effect in the proposed method is measured according to the variation in crowd particle numbers in the image nodes; characteristics of the crowd following a general trend are incorporated by adjusting the particle directions. The model predicts dense crowd abnormal events in different intervals through iterations of simultaneous streaming and collision steps. Few initial frames of a video are needed to initialize the proposed model and no training procedure is required. Experimental results show that our purpose-driven LBM performs better than most state-of-the-art methods.

A large eddy based lattice-Boltzmann simulation of velocity distribution in an open channel flow with rigid and flexible vegetation

Gac J.

Acta Geophysica

2014

Vol. 62, no. 1

180--198

The large eddy simulation method, based on a lattice-Boltzmann algorithm, was used to compute the vertical velocity profile in an open channel flow with submerged and emerged vegetation. The numerical method is characterized by the relatively short time of computation and low complexity. On the other hand, it allows a more realistic description of the vegetation properties relative to the methods commonly used in 1-D numerical models. For the proper conditions, the method developed in this work gives results similar to other numerical methods. These results are also in good agreement with the experimental data presented in other papers.