A Skeleton-based Approach for Campus Violence Detection  

作　　者：Batyrkhan Omarov Sergazy Narynov Zhandos Zhumanov Aidana Gumar Mariyam Khassanova 

机构地区：[1]Alem Research,Almaty,Kazakhstan [2]Al-Farabi Kazakh National University,Almaty,Kazakhstan [3]International University of Tourism and Hospitality,Turkistan,Kazakhstan [4]Suleiman Demirel University,Almaty,Kazakhstan [5]Asfendiyarov Kazakh National Medical University,Almaty,Kazakhstan

出　　处：《Computers, Materials & Continua》2022年第7期315-331,共17页计算机、材料和连续体（英文）

基　　金：This work was supported by the grant“Development of artificial intelligenceenabled software solution prototype for automatic detection of potential facts of physical bullying in educational institutions”funded by the Ministry of Education of the Republic of Kazakhstan.Grant No.IRN AP08855520.

摘　　要：In this paper,we propose a skeleton-based method to identify violence and aggressive behavior.The approach does not necessitate highprocessing equipment and it can be quickly implemented.Our approach consists of two phases:feature extraction from image sequences to assess a human posture,followed by activity classification applying a neural network to identify whether the frames include aggressive situations and violence.A video violence dataset of 400 min comprising a single person’s activities and 20 h of video data including physical violence and aggressive acts,and 13 classifications for distinguishing aggressor and victim behavior were generated.Finally,the proposed method was trained and tested using the collected dataset.The results indicate the accuracy of 97%was achieved in identifying aggressive conduct in video sequences.Furthermore,the obtained results show that the proposed method can detect aggressive behavior and violence in a short period of time and is accessible for real-world applications.

关 键 词：PoseNET SKELETON VIOLENCE BULLYING artificial intelligence machine learning 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]