视频浓缩中的优化目标函数研究

详细信息    查看全文 | 推荐本文 |

英文篇名：Research on the optimal objective function in video synopsis 作者：唐世杰 ; 周越 ; 尚岩峰 英文作者：TANG Shi-jie;3ZHOU Yue;SHANG Yan-feng;School of Electronic Information & Electrical Engineering,Shanghai Jiaotong University;The Third Research Institute of Ministry of Public Security;Shanghai Engineering Research Center of Intelligent Video Surveillance; 关键词：视频浓缩 ; 目标数分布 ; 优化目标函数 ; 差分进化算法 ; 轨迹排布 英文关键词：video synopsis;;target number distribution;;optimal objective function;;differential evolution algorithm;;arrangement of tracklet sets 中文刊名：HDZJ 英文刊名：Information Technology 机构：上海交通大学电子信息与电气工程学院;公安部第三研究所;上海智能视频监控工程技术研究中心; 出版日期：2018-01-24 出版单位：信息技术 年：2018 基金：公安部警用装备论证项目(C17304);; 江苏省科技支撑计划项目(SS201413) 语种：中文; 页：HDZJ201801005 页数：5 CN：01 ISSN：23-1557/TN 分类号：18-21+27

摘要

现有的视频浓缩方法普遍存在一个问题,即浓缩视频画面中包含的目标太多,不适合审阅。从视频浓缩效果的评价标准出发,提出了更合适的评价标准,改进了优化目标函数;即期望更少重叠、更少时序混乱的情况下,期望同时出现的目标数为5~9个。另外,采用差分进化算法搜索近似最优的轨迹排布。实验表明,改进后的算法有效解决了上述问题。
        There is a common problem in the existing video synopsis methods,that is,the screen of the concentrated video contains too many targets,not suitable for review. Based on the evaluation criteria of video synopsis,this paper put forward a more appropriate evaluation criterion and improved the objective function; namely,the expected number of targets that are expected to occur at the same time is 5-9,with less overlap and less sequence confusion. In addition,the paper used differential evolution algorithm to search the approximate optimal arrangement of tracklet sets. The experimental results show that the improved algorithm can solve the above problem effectively.

引文

[1]Making a Long Video Short:Dynamic Video Synopsis[C].CVPR'06,Jun.2006:435-441.
    [2]Pritch Y,Rav-Acha A,Peleg S.Nonchronological video synopsis and indexing[C]∥IEEE Transactions on Software Engineering,2008:1971-1984.
    [3]Fu W,Wang J,Gui L,et al.Online video synopsis of structured motion[J].Neurocomputing,2014,135(8):155-162.
    [4]Vural U,Akgul YS.Eye-gaze based real-time surveillance video synopsis[J].Pattern Recognition Letters,2009,30:1151-1159.