Research Article
Recognition of Human Abnormal Behavior in Static Image of Intelligent Monitoring System Based on Neural Network Algorithm
@INPROCEEDINGS{10.1007/978-3-030-94182-6_20, author={Hai-jing Zhou}, title={Recognition of Human Abnormal Behavior in Static Image of Intelligent Monitoring System Based on Neural Network Algorithm}, proceedings={IoT and Big Data Technologies for Health Care. Second EAI International Conference, IoTCare 2021, Virtual Event, October 18-19, 2021, Proceedings, Part II}, proceedings_a={IOTCARE PART 2}, year={2022}, month={6}, keywords={Neural Network Intelligent monitoring Static image Behavior recognition}, doi={10.1007/978-3-030-94182-6_20} }- Hai-jing Zhou
Year: 2022
Recognition of Human Abnormal Behavior in Static Image of Intelligent Monitoring System Based on Neural Network Algorithm
IOTCARE PART 2
Springer
DOI: 10.1007/978-3-030-94182-6_20
Abstract
In recent years, human abnormal behavior recognition in static images is a hot topic in the vision field of intelligent monitoring system. In order to achieve the goal of accurate recognition of human abnormal behavior in static images, a method of human abnormal behavior recognition in static images of intelligent monitoring system based on neural network algorithm is proposed. The pedestrian detection algorithm based on neural network algorithm for filtering channel features is used to locate each target human body, collect feature data and denoise. Then the appearance model of each human structure feature frame is constructed, and finally the neural network algorithm is used for behavior classification and recognition. The experimental results show that the human abnormal behavior recognition method based on neural network algorithm in the static image of intelligent monitoring system can recognize the behavior of multiple human bodies in a single frame image. This method can provide multi category classification of human abnormal behavior at the same time, the experimental effect is obvious, and the accuracy is high.
