Crowd Sexual Behavior Recognition Methods in Video Data

The identification of crowd sexual behaviors in video surveillance systems has always been a hot research topic for scholars at home and abroad. In view of the lack of knowledge management and fusion in the existing research and the redundancy of sub-algorithms, this book mainly uses the pedestrian primitives in the video image as the minimum granularity to study the pedestrian skeleton attribute information and the number of attribute information; and according to the relationship between pedestrian attribute information, the abnormal behavior of pedestrians is modeled based on fuzzy logic rules, and the validity of the model algorithm is tested by examples. This research belongs to the intersection and penetration of social public security management, emergency management, big data mining and artificial intelligence, and has certain theoretical and practical significance for realizing pedestrian group behavior recognition under surveillance video big data.This book can be read and referenced by researchers in related fields such as public security management and big data.