[1]刘 清,吴志刚,窦 琴,等.粒子滤波的视频目标跟踪算法研究[J].智能系统学报,2009,4(6):538-543.[doi:10.3969/j.issn.1673-4785.2009.06.012]
LIU Qing,WU Zhi-gang,DOU Qin,et al.A particle filtering algorithm for tracking moving objects in videos[J].CAAI Transactions on Intelligent Systems,2009,4(6):538-543.[doi:10.3969/j.issn.1673-4785.2009.06.012]
点击复制
LIU Qing,WU Zhi-gang,DOU Qin,et al.A particle filtering algorithm for tracking moving objects in videos[J].CAAI Transactions on Intelligent Systems,2009,4(6):538-543.[doi:10.3969/j.issn.1673-4785.2009.06.012]
粒子滤波的视频目标跟踪算法研究
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
4
期数:
2009年第6期
页码:
538-543
栏目:
学术论文—智能系统
出版日期:
2009-12-25
- Title:
- A particle filtering algorithm for tracking moving objects in videos
- 文章编号:
- 1673-4785(2009)06-0538-06
- Keywords:
- object tracking; particle filter; integral image; foreground segmentation; video
- 分类号:
- TP18；TP391.4
- 文献标志码:
- A
- 摘要:
- 目标跟踪是计算机视觉和图像处理的一个重点课题，在视频监控、机器人视觉导航以及智能交通控制中具有广泛的应用前景.通过粒子滤波技术，研究了如何整合颜色特征、前景信息和积分图运算等技术实现视频目标跟踪的粒子滤波算法.在对目标进行分割中采用了混合高斯背景建模方法；同时结合积分直方图的计算方法对颜色特征进行分段统计及相互遮挡的判断，实现基于粒子滤波的目标跟踪算法的优化，解决跟踪中诸如遮挡、光照变化、背景干扰、尺寸变化等难以解决的问题.实验结果表明提出的方法达到了预期目标.
- Abstract:
- Tracking moving objects across video sequences is a key subject in computer vision and image processing. It is required for fields as diverse as video surveillance, robotic vision, navigation, and intelligent traffic control. After studying particle filter technology, a moving object tracking algorithm based on a particle filter was developed, integrating foreground information, color features and an integral image method. Gaussian mixture models (GMM) were employed for object foreground segmentation. By using an integral histogram algorithm, data for the color features in different sections were derived. Based on the feature’s integral histogram, occlusion could then be analyzed and judged. The method presented can resolve occlusion caused by objects appearing among obstacles or with other objects, and to some extent overcome problems caused by changes in illumination, background and apparent size. Experimental results when tracking moving objects agreed well with predicted results.
- 参考文献/References:
-
［1］GORDON N. A hybrid bootstrap filter for target tracking in clutter［J］.IEEE Trans on AES， 1997, 33 (1):353-358.
［2］GORDON N, SALMOND D, SMITH A. Novel approach to nonlinear nonGaussian Bayesian state estimation［J］. IEEE Proceedings on Radar and Signal Processing, 1993, 140: 107-113.
［3］GODSILL D S, ANDRIE C. On sequential Monte Carlo sampling methods for Bayesian filtering［J］. Statistics and Computing,2000， 10(3):197-208.
［4］XU Dongbin, HUANG Lei, LIU Changping. Object tracking using particle filter based on color correlogram［C］//Second International Symposium on Intelligent Information Technology Application 2008, Shanghai,2008: 477-480.
［5］ZHUANG Yan, WANG Wei, XING Ruizhi. Target tracking in colored image sequence using weighted color histogram based particle filter［C］//IEEE International Conference on Robotics and Biomimetics 2006, Kunming，17-20:1488-1493.
［6］LOZA A, PATRICIO M A, GARCIA J, MOLINA J M. Advanced algorithms for realtime video tracking with multiple targets［C］//International Conference on Control, Automation, Robotics, and Vision. Hanoi, Vietnam, 2008, 17-20: 125-131.
［7］陆 军,李凤玲,姜 迈.摄像机运动下的动态目标检测与跟踪［J］. 哈尔滨工程大学学报,2008,29(8):831-835.
LU Jun, LI Fengling, JIANG Mai.Detection and tracking of moving targets with a moving camera［J］. Journal of Harbin Engineering University, 2008,29(8):831-835.
［8］焦安霞, 姜 弢. 视频序列中动目标快速跟踪新算法的研究［J］. 应用科技,2008,35(12):7-10.
JIAO Anxia, JIANG Tao. A fast tracking algorithm for video sequence moving object［J］. Applied Science and Technology, 2008,35(12):7-10.
［9］邓文坛,张三同,余 纯. 一种改进的粒子滤波跟踪算法的研究［J］. 自动化技术与应用,2008,27(3):84-87.
DENG Wentan, ZHANG Santong, YU Chun. A modified particle filtering algorithm for tracking［J］. Techniques of Automation and Applications, 2008,27(3):84-87.
［10］王 健, 金永镐, 董华春, 权太范. 进化粒子滤波算法在雷达目标跟踪中的应用［J］. 现代防御技术,2007,36(2):115-118.
WANG jian, JIN Yonghao, DONG Huachun, QUAN Taifan. Evolutionary particle filter algorithm in radar target tracking［J］. Modern Defence Technology, 2007,36(2):115-118.
- 相似文献/References:
-
[1]伍 明,孙继银.一种机器人未知环境下动态目标跟踪交互多模滤波算法[J].智能系统学报,2010,5(2):127.
WU Ming,SUN Ji-yin.An interacting multiple model filtering algorithm for mobile robots to improve tracking of moving objects in unknown environments[J].CAAI Transactions on Intelligent Systems,2010,5():127.
[2]杨 戈,刘 宏.视觉跟踪算法综述[J].智能系统学报,2010,5(2):95.
YANG Ge,LIU Hong.Survey of visual tracking algorithms[J].CAAI Transactions on Intelligent Systems,2010,5():95.
[3]李 金,胡文广.基于颜色的快速人体跟踪及遮挡处理[J].智能系统学报,2010,5(4):353.
LI Jin,HU Wen-guang.Tracking fast movement using colors while accommodating occlusion[J].CAAI Transactions on Intelligent Systems,2010,5():353.
[4]海 丹,李 勇,张 辉,等.无线传感器网络环境下基于粒子滤波的移动机器人SLAM算法[J].智能系统学报,2010,5(5):425.[doi:10.3969/j.issn.1673-4785.2010.05.008]
HAI Dan,LI Yong,ZHANG Hui,et al.Simultaneous localization and mapping of a mobile robot in wireless sensor networks based on particle filtering[J].CAAI Transactions on Intelligent Systems,2010,5():425.[doi:10.3969/j.issn.1673-4785.2010.05.008]
[5]韩华,丁永生,郝矿荣.综合颜色和小波纹理特征的免疫粒子滤波视觉跟踪[J].智能系统学报,2011,6(4):289.
HAN Hua,DING Yongsheng,HAO Kuangrong.An immune particle filter video tracking method based on color and wavelet texture[J].CAAI Transactions on Intelligent Systems,2011,6():289.
[6]刘侠,陶冶,邢春.统计差分与自启动的Camshift跟踪算法[J].智能系统学报,2011,6(4):355.
LIU Xia,TAO Ye,XING Chun.An objective tracking Camshift algorithm based onautomatic startup and the statistical differential method[J].CAAI Transactions on Intelligent Systems,2011,6():355.
[7]伍明,孙继银.基于粒子滤波的未知环境下机器人同时定位、地图构建与目标跟踪[J].智能系统学报,2013,8(2):168.[doi:10.3969/j.issn.1673-4785.201202001]
WU Ming,SUN Jiyin.Simultaneous localization, mapping and object tracking in an unknown environment using particle filtering[J].CAAI Transactions on Intelligent Systems,2013,8():168.[doi:10.3969/j.issn.1673-4785.201202001]
[8]贺超,刘华平,孙富春,等.采用Kinect的移动机器人目标跟踪与避障[J].智能系统学报,2013,8(5):426.[doi:10.3969/j.issn.1673-4785.201301028]
HE Chao,LIU Huaping,SUN Fuchun,et al.Target tracking and obstacle avoidance of mobile robot using Kinect[J].CAAI Transactions on Intelligent Systems,2013,8():426.[doi:10.3969/j.issn.1673-4785.201301028]
[9]王熙,吴为,钱沄涛.基于轨迹聚类的超市顾客运动跟踪[J].智能系统学报,2015,10(2):187.[doi:10.3969/j.issn.1673-4785.201401002]
WANG Xi,WU Wei,QIAN Yuntao.Trajectory clustering based customer movement tracking in a supermarket[J].CAAI Transactions on Intelligent Systems,2015,10():187.[doi:10.3969/j.issn.1673-4785.201401002]
[10]王尔申,李兴凯,庞涛.基于BP神经网络的粒子滤波算法[J].智能系统学报,2014,9(6):709.[doi:10.3969/j.issn.1673-4785.201310057]
WANG Ershen,LI Xingkai,PANG Tao.A particle filtering algorithm based on the BP neural network[J].CAAI Transactions on Intelligent Systems,2014,9():709.[doi:10.3969/j.issn.1673-4785.201310057]
[11]王绍钰 蔡自兴,陈爱斌.改进的粒子滤波器目标跟踪方法[J].智能系统学报,2008,3(3):189.
WANG Shao-yu,CAI Zi-xing,CHEN Ai-bin.Improved object tracking method for particle filters[J].CAAI Transactions on Intelligent Systems,2008,3():189.
[12]陈真,王钊.元认知粒子滤波目标跟踪算法[J].智能系统学报,2015,10(3):387.[doi:10.3969/j.issn.1673-4785.201405052]
CHEN Zhen,WANG Zhao.Object tracking algorithm with metacognitive model-based particle filters[J].CAAI Transactions on Intelligent Systems,2015,10():387.[doi:10.3969/j.issn.1673-4785.201405052]
[13]刘峰,宣士斌,刘香品.佳点集的QMC粒子滤波算法及其应用[J].智能系统学报,2014,9(4):461.[doi:10.3969/j.issn.1673-4785.201305079]
LIU Feng,XUAN Shibin,LIU Xiangpin.Quasi-Monte Carlo particle filter algorithm based on the good point set and its application[J].CAAI Transactions on Intelligent Systems,2014,9():461.[doi:10.3969/j.issn.1673-4785.201305079]
[14]许奇,王华彬,周健,等.用于目标跟踪的智能群体优化滤波算法[J].智能系统学报,2019,14(4):697.[doi:10.11992/tis.201805049]
XU Qi,WANG Huabin,ZHOU Jian,et al.Swarm intelligence filtering for robust object tracking[J].CAAI Transactions on Intelligent Systems,2019,14():697.[doi:10.11992/tis.201805049]
备注/Memo
收稿日期：2009-09-21.
基金项目：高等学校博士学科点专项科研基金资助项目（20060497017）；湖北省自然科学基金资助项目(2009CDB403).
作者简介：
刘 清，女，1966年生，教授，博士，主要研究方向为智能控制技术、智能移动机器人、智能视频监控、计算机实时控制和信息系统集成.
更新日期/Last Update:
2010-02-22