A Skeleton-based Approach for Campus Violence Detection

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

作者机构：Alem ResearchAlmatyKazakhstan Al-Farabi Kazakh National UniversityAlmatyKazakhstan International University of Tourism and HospitalityTurkistanKazakhstan Suleiman Demirel UniversityAlmatyKazakhstan Asfendiyarov Kazakh National Medical UniversityAlmatyKazakhstan 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第72卷第7期

页      面：315-331页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

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 

主　　题：PoseNET skeleton violence bullying artificial intelligence machine learning 

摘      要：In this paper,we propose a skeleton-based method to identify violence and aggressive *** approach does not necessitate highprocessing equipment and it can be quickly *** 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 ***,the proposed method was trained and tested using the collected *** results indicate the accuracy of 97%was achieved in identifying aggressive conduct in video ***,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.