时间：2020-05-19
本文（Irregular Action Recognition in Court With 3D Residual Network）原载2020 IEEE 5th International Conference on Cloud Computing and Big Data Analytics，由四川大学王竹教授等科研人员创作，系四川大学市场经济法治研究所系列学术成果。后续会持续分享四川大学市场经济法治研究所系列学术成果，欢迎大家阅读。
Several irregular behaviors, such as smoking, absent and dozing, sometimes occur in the court. To ensure the participants in court in order without irregular behaviors is of importance for a regular trial. However, manually handling such numerous surveillance videos to discriminate and prevent irregular actions is a mission impossible. Recently many effective action recognition algorithms had been proposed, which brings opportunity to overcome the difficulty. We take into account the particularities of irregular actions in court, i.e. stationary background and small range of motion, and thus propose our irregular action recognition method based on 3D residual network that focuses on modeling spatiotemporal information of motion in videos. Experiments show our method can achieve a recognition rate of 82.3% on 13 classes of irregular actions in court.
Song Liu, Qiaolin He, Zhu Wang, Yifei Pu, and Yi Zhang. Irregular Action Recognition in Court With 3D Residual Network, 2020 IEEE 5th International Conference on Cloud Computing and Big Data Analytics, 2020, pp. 403-407.（论文下载）
