Abstract
Sparse representation method has been well used in image analysis, restoration and recognition, and it has also been introduced to analysis of video crowd movements recent years. To improve its accuracy of detecting abnormal events in crowd videos, a double sparse representation method is proposed. The method has two sparse processes, one of them judges whether the region of interest is normal, the other finds out whether the region is abnormal. The two judgments will be processed by fuzzy integral to obtain a final result for this region. Experiments are proceed in different datasets to validate the advantages of our algorithm. The results show that our method achieves higher accuracy than previous methods which are used for analysis of video crowd movements.
J. Jiang—The work is supported by the National Natural Science Foundation of China (Projects No. 61171184 and 61201309).
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Jiang, J., Tao, Y., Zhao, W., Tang, X. (2015). Abnormal Crowd Motion Detection Using Double Sparse Representations. In: He, X., et al. Intelligence Science and Big Data Engineering. Image and Video Data Engineering. IScIDE 2015. Lecture Notes in Computer Science(), vol 9242. Springer, Cham. https://doi.org/10.1007/978-3-319-23989-7_26
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