【摘要】 大量的研究行为识别方法集中在检测简单的动作,如:步行,慢跑或者跳跃等;针对于打斗或者动作复杂的攻击性行为则研究较少;而这些研究在某些监控场景下非常有用,如:监狱,自助银行,商场等.传统的暴力行为识别研究方法主要利用先验知识来手动设计特征,而本文提出了一种基于3D-CNN结构的暴力检测方法,通过三维深度神经网络直接对输入进行操作,能够很好的提取暴力行为的时空特征信息,从而进行检测.从实验结果可以看出,本文方法能较好地识别出暴力行为,准确率要高于人工设计特征的方法.更多还原

【Abstract】 A large number of research behavioral methods are focused on detecting simple actions such as walking,jogging,or jumping,while less research is on violence or aggressive behavior,but these studies are useful in some surveillance scenarios,such as:Prison,self-help banks,shopping malls and so on.Traditional methods of violent behavior recognition research mainly use a priori knowledge to manually design features.In this paper a violence detection method based on 3D-CNN structure is proposed.The three-dimensional deep neural network directly manipulates on the input,which can be a good extraction of violent behavior of time and space characteristics of information.It can be seen from the experimental results that this method can identify the violent behavior better than the characteristics of hand-craft features.更多还原