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- W2357577997 abstract "A recognition method of dangerous actions in bus was proposed in the paper,based on the behavior visual optimization analysis. The maximum similarity clustering method was used to accurately segment the human motion image in the monitoring images in bus,to eliminate a large number of interference characteristics of irrelevant personnel. The clustering function of human movement was fitted,and the main curvature of the edge location of human movement was calculated,to get the location and scale of the human movement. Human movements were adaptively classified using gray level co-occurrence matrix,in order to complete rapid and accurate identification of dangerous actions. The experimental results show that using the improved algorithm can accurately identify the dangerous actions of passengers in bus,and the efficiency improvement is obvious." @default.
- W2357577997 created "2016-06-24" @default.
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- W2357577997 date "2015-01-01" @default.
- W2357577997 modified "2023-09-25" @default.
- W2357577997 title "Simulation of Visual Image Recognition of Dangerous Actions in Buses" @default.
- W2357577997 hasPublicationYear "2015" @default.
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