Research Article
Campus Bullying Detecting Algorithm Based on Surveillance Video
@INPROCEEDINGS{10.1007/978-3-030-69066-3_27, author={Liang Ye and Susu Yan and Tian Han and Tapio Sepp\aa{}nen and Esko Alasaarela}, title={Campus Bullying Detecting Algorithm Based on Surveillance Video}, proceedings={Artificial Intelligence for Communications and Networks. Second EAI International Conference, AICON 2020, Virtual Event, December 19-20, 2020, Proceedings}, proceedings_a={AICON}, year={2021}, month={7}, keywords={Campus bullying bone points Openpose Support vector machine}, doi={10.1007/978-3-030-69066-3_27} }- Liang Ye
Susu Yan
Tian Han
Tapio Seppänen
Esko Alasaarela
Year: 2021
Campus Bullying Detecting Algorithm Based on Surveillance Video
AICON
Springer
DOI: 10.1007/978-3-030-69066-3_27
Abstract
In recent years, more and more violent events are taking place in campus life. Campus bullying prevention is already the focus of current education. This paper proposes a campus bullying detecting algorithm based on surveillance video. It can actively monitor whether students are being bullied on campus. The authors use Openpose to extract bone information from video. According to the coordinate information of bone points, they extract static and dynamic features. Support vector machine (SVM) is used to classify different actions. The recognition accuracy of the classification model is 88.57%. In this way, the campus surveillance camera is able to realize real-time monitoring of bullying behavior. It is conducive to the construction of a harmonious campus environment.