Smoking behavior detection is of great significance for ensuring the equipment operation conditions,operators'life and property safety in the production area of thermal power generation enterprises.At present,smoking behavior detection is mainly based on the detection of cigarette targets.However,in the production areas of thermal power plants,most of the camaras are of low-definition and installed for large scenes.The cigarettes in the monitoring videos are very small targets,with difficulty in detection and low accuracy of detection.In order to solve the above problems,this paper proposes a smoking behavior analysis method based on facial state analysis.First,the human face appearing in the monitoring video is detected,and the status of the human face is analyzed.By determining whether a person's face covered by his hands is a smoking-like posture,the accuracy of detection is improved by judging the relative positions of face,human body and hand.Then,time series processing module is used to analyze the state of human face in a period of time.When the frequency of smoking-like gestures within a certain period of time is greater than a set threshold,smoking behavior can be identified and an alarm is issued.Experimental results show that the precision rate,recall rate,and average detection time of this method in industrial scenes are better than the existing smoking behavior detection algorithms.
关键词
工业场景/吸烟检测/目标检测/时序处理模块/行为分析
Key words
industrial scene/smoking detection/target detection/time series processing module/behavior analysis
维普
万方数据