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所属单位：计算机科学与技术学院/人工智能学院/软件学院
发表刊物：Lect. Notes Comput. Sci.
摘要：Violence detection in videos is of great importance in many applications, ranging from teenagers protection to online media filtering and searching to surveillance systems. Typical methods mostly rely on hand-crafted features, which may lack enough discriminative capacity for the specific task of violent action recognition. Inspired by the good performance of deep models for human action recognition, we propose a novel method for detecting human violent behaviour in videos by integrating trajectory and deep convolutional neural networks, which takes advantage of hand-crafted features [21] and deep-learned features [23]. To evaluate this method, we carry out experiments on two different violence datasets: Hockey Fights dataset and Crowd Violence dataset. The results demonstrate the advantage of our method over state-of-the art methods on these datasets. © 2017, Springer International Publishing AG.
ISSN号：0302-9743
是否译文：否
发表时间：2017-01-01
合写作者：Meng, Zihan,李震
通讯作者：Meng, Zihan,袁家斌