Violence region localization in video and the school violent actions classification

IF 2.4 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Ngo Duong Ha, Nhu Y. Tran, Le Nhi Lam Thuy, Ikuko Shimizu, Pham The Bao
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引用次数: 0

Abstract

Classification of school violence has been proven to be an effective solution for preventing violence within educational institutions. As a result, technical proposals aimed at enhancing the efficacy of violence classification are of considerable interest to researchers. This study explores the utilization of the SORT tracking method for localizing and tracking objects in videos related to school violence, coupled with the application of LSTM and GRU methods to enhance the accuracy of the violence classification model. Furthermore, we introduce the concept of a padding box to localize, identify actions, and recover tracked objects lost during video playback. The integration of these techniques offers a robust and efficient system for analyzing and preventing violence in educational environments. The results demonstrate that object localization and recovery algorithms yield improved violent classification outcomes compared to both the SORT tracking and violence classification algorithms alone, achieving an impressive accuracy rate of 72.13%. These experimental findings hold promise, especially in educational settings, where the assumption of camera stability is justifiable. This distinction is crucial due to the unique characteristics of violence in educational environments, setting it apart from other forms of violence.
视频中的暴力区域定位与校园暴力行为分类
事实证明,对校园暴力进行分类是预防教育机构内暴力的有效办法。因此,旨在提高暴力分类效果的技术建议引起了研究人员的极大兴趣。本研究探索利用SORT跟踪方法对校园暴力相关视频中的对象进行定位和跟踪,并结合LSTM和GRU方法的应用,提高暴力分类模型的准确性。此外,我们引入了填充盒的概念来定位,识别动作,并恢复在视频播放过程中丢失的跟踪对象。这些技术的整合为分析和预防教育环境中的暴力提供了一个强大而有效的系统。结果表明,与单独使用SORT跟踪和暴力分类算法相比,目标定位和恢复算法产生了更好的暴力分类结果,达到了令人印象深刻的72.13%的准确率。这些实验结果带来了希望,特别是在教育环境中,相机稳定性的假设是合理的。这一区别至关重要,因为教育环境中的暴力具有独特的特征,使其有别于其他形式的暴力。
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来源期刊
Frontiers in Computer Science
Frontiers in Computer Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.30
自引率
0.00%
发文量
152
审稿时长
13 weeks
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