A method of video target's trajectory analysis based on HMM clustering
Jianjun Jia · Journal of North China Electric Power University · 2010
A novel motion trajectory pattern learning and anomaly detection method based on HMM clustering was put forward for the problem of moving target's behavior analysis in visual surveillance system.Firstly,one HMM was trained for each trajectory in the training set and the pair-wise distance between the models was calculated to measure the difference of the trajectories;then,the rows of the pair-wise distance matrix,after processed by PCA,were taken as the features of the corresponding trajectories and clustered through fuzzy C-means method and different HMMs were trained for each cluster of the trajectories to represent their distribution patterns;finally a mechanism was given to detect the anomaly through the learned models.The experiment on the trajectories of different scenes shows its effectiveness.