基于区域时空二合一网络的动作检测方法  

Action Detection Based on Region Spatiotemporal Two-in-One Network

作　　者：汤强 朱煜[1] 郑兵兵[1] 郑婕 TANG Qiang;ZHU Yu;ZHENG Bingbing;ZHENG Jie(School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China)

机构地区：[1]华东理工大学信息科学与工程学院,上海200237

出　　处：《华东理工大学学报（自然科学版）》2022年第1期105-111,共7页Journal of East China University of Science and Technology

摘　　要：视频动作检测研究是在动作识别的基础上进一步获取动作发生的位置和时间信息。结合RGB空间流和光流时间流,提出了一种基于SSD的区域时空二合一动作检测网络。改进了非局部时空模块,在光流中设计了像素点筛选器来提取运动关键区域信息,只对空间流中筛选出的动作关键区域进行相关性计算,有效获得动作长距离依赖并改善非局部模块计算成本较大的缺陷,同时降低了视频背景噪声的干扰。在基准数据集UCF101-24上进行了实验,结果表明所提出的区域时空二合一网络具有更好的检测性能,视频级别的平均精度(video_AP)达到了43.17%@0.5。With the explosive growth of video data,video intelligent analysis has been becoming the academic and industrial research hotspot.The objective of video action detection is to obtain the location and time information of actions based on action recognition.By combining the single shot multi-box detector(SSD)with the RGB space flow and optical flow,this paper proposes a region spatiotemporal two-in-one action detection network.To improve the nonlocal spatiotemporal module in the network,a pixel filter is proposed in optical flow to extract the information of key motion regions,and then,the correlation calculation is performed only on the selected key motion regions in the spatial flow.The proposed module can get long-range dependence of actions effectively and reduce the computational cost of the nonlocal module and the interference of video background noise.Finally,the proposed network is tested on the benchmark dataset UCF101-24,and attain better detection performance.

关 键 词：视频动作检测 SSD 双流网络 非局部模块 UCF101-24 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]