nav emailalert searchbtn searchbox tablepage yinyongbenwen piczone journalimg journalInfo journalinfonormal searchdiv searchzone qikanlogo popupnotification paper paperNew
165 2,810 313
阅读 下载 被引

工具集

引用本文 下载本文
PDF
引用导出 分享

    扫码分享到微信或朋友圈

使用微信“扫一扫”功能。
将此内容分享给您的微信好友或者朋友圈
摘要:

视频监控技术为重要场所安全防护提供了可靠保障,随着视频监控系统应用领域的扩大,视频监控技术得到了迅速发展。首先对视频监控技术的发展历程分三个阶段进行了概括,其次对视频监控中的关键技术的现状和发展方向进行了分析,其中重点描述了运动检测中的主流方法———背景差方法,目标跟踪中用于解决遮挡问题的合并分裂方法和直接穿透方法,最后提出了视频监控技术在实际应用中所面临的问题。

Abstract:

The technology of video surveillance enhances the secure reliability in important situations and it is developed rapidly with the expansion of its application in various areas.This paper reviews its history by three stages at first,then analyzes its status at present and development trends by focusing on the background subtraction techniques that are commonly used in motion detection,the merge-split approach and the straight-through approach that deal with occlusion in target tracking,presents the most urgent issues in its application in conclusion.

参考文献

[1]Boghossian B,Velastin S.Image Processing System for Pe-destrian Monitoring Using Neural Classification of NormalMotion Patterns[J].Measurement and Control,1999,32(9):261 264.

[2]Boghossian B,Velastin S.Motion based Machine VisionTechniques for the Management of Large Crowds[C].IEEE6th International Conference on Electronics,Circuits andSystems,Pafos,Cyprus,1999.

[3]Collins R.A System for Video Surveillance and Monitoring:VSAM Final Report.Carnegie Mellon University,TechnicalReport:CMU RI TR 00 12,2000.

[4]Omar Javed,Mubarak Shah.KNIGHTM A Real Time Sur-veillance System.http://www.cs.ucf.edu/vision/papers/Javed Shah ITS2003.pdf.

[5]Arun Hampapur.S3 R1:The IBM Smart Surveillance Sys-tem Release 1.IBM T.J.Watson Research Center.

[6]Remagnino P,Tan T,Baker K.Multi agent Visual Surveil-lance of Dynamic Scenes[J].Image and Vision Computing,1998,16(8):529 532.

[7]Manzanera A,Richefeu J.A Robust and Computationally Ef-ficient Motion Detection Algorithm Based onΣΔBackground Estimation.In ICVGIP,Kolkata,India,2004.

[8]Richefeu J,Manzanera A.A New Hybrid Differential Filterfor Motion Detection.ICCVG′04,Warsaw,Poland,2004:22 24.

[9]Stauffer C,Grimson E.Learning Patterns of Activity UsingReal Time Tracking[J].IEEE Transactions on PatternRecognition and Machine Intelligence(TPAMI),2000,22(8):747 757.

[10]Stauffer C,Grimson W E L.Adaptive Background MixtureModels for Real Time Tracking.in Proc.Computer Visionand Pattern Recognition 1999(CVPR′99),1999.

[11]Elgammal A,Harwood D,Davis L.Non parametric Modelfor Background Subtraction.in Proc.of ICCV′99 Framerate Workshop,1999.

[12]Oliver N M,Rosario B,Pentland A P.A Bayesian Comput-er Vision System for Modeling Human Interactions[J].IEEE Trans.on Patt.Anal.and Machine Intell.,2000,22(8):831 843.

[13]Han B,Comaniciu D,Davis L.Sequential Kernel DensityApproximation through Mode Propagation:Applications toBackground Modeling[C].Proc.ACCV Asian Conf.onComputer Vision,2004.

[14]Haritaoglu I,Harwood D,Davis L S.W4:Real Time Sur-veillance of People and Their Activities[J].IEEE Trans.Pattern Analysis and Machine Intelligence,2000,22(8):809 830.

[15]Javed O,Shafique K,Shah M.A Hierarchical Approach toRobust Background Subtraction using Color and GradientInformation.IEEE Workshop on Motion and Video Compu-ting,Orlando,2002.

[16]Javed O,Shah M.Tracking And Object Classification For Au-tomated Surveillance[C].The Seventh European Conference onComputer Vision(ECCV 2002),Copenhagen,2002.

[17]Javed O,Rasheed Z,Alatas O,et al.KNIGHTM:A RealTime Surveillance System for Multiple Overlapping andNon Overlapping Cameras[C].IEEE International Con-ference on Multimedia and Expo(ICME 2003),Baltimore,Maryland,USA,2003.

[18]Cucchiara R,Grana C,Piccardi M,et al.Detecting MovingObjects,Ghosts and Shadows in Video Streams[J].IEEETrans.on Patt.Anal.and Machine Intell.,2003,25(10):1 337 1 342.

[19]Cucchiara R,Grana C,Piccardi M,et al.Detecting Objects,Shadows and Ghosts in Video Streams by Exploiting Colorand Motion Information[A].Proc of IEEE Int′l Conferenceon Image Analysis and Processing[C].[s.l.]:IEEE,2001:360 365.

[20]Tian Y L,Lu M,Hampapur A.Robust and Efficient Fore-ground Analysis for Real Time Video Surveillance.CVPR,2005,(1):1 182 1 187.

[21]Koller D,Danilidis K,Nagel H.Model based ObjectTracking in Monocular Image Sequences of Road TrafficScenes[J].Int.J.Comput.Vis.,1993,10(3):257 281.

[22]Gu C,Lee M C.Semiautomatic Segmentation and Trackingof Semantic Video Objects[J].IEEE Trans.Circuits Syst.Video Technol.,1998,8(5):572 584.

[23]Zhao J W,Wang P,Liu C Q.An Object Tracking Algo-rithm Based on Occlusion Mesh Model[C].in Proc.Int.Conf.Machine Learning and Cybernetics,2002:288 292.

[24]Sun S,Haynor D R,Kim Y.Semiautomatic Video ObjectSegmentation Using VSnakes[J].IEEE Trans.CircuitsSyst.Video Technol.,2003,13(1):75 82.

[25]Jang D S,Choi H I.Active Models for Tracking MovingObjects[J].Pattern Recognition,2000,33(7):1 135 1 146.

[26]Segen J,Pingali S.A Camera based System for TrackingPeople in Real Time[C].Proc International Conference onPattern Recognition,Vienna,1996:63 67.

[27]Pierre F Gabriel,Jacques G Verly,Justus H Piater,et al.The State of the Art in Multiple Object Tracking UnderOcclusion in Video Sequences.

[28]Haritaoglu I.A Real Time System for Detection and Track-ing of People and Recognizing Their Activities.PHD Pro-posal,University of Maryland,1998.

[29]Piater J H,Crowley J L.Multi modal Tracking of Interac-ting Targets Using Gaussian Approximations[M].SecondIEEE International Workshop on Performance Evaluationof Tracking and Surveillance,2001.

[30]McKenna S,Jabri S,Duric Z,et al.Tracking Groups ofPeople[M].Computer Vision and Image Understanding,2000.

[31]Brémond F,Thonnat M.Tracking Multiple Nonrigid Ob-jects in Video Sequences.IEEE Trans.on Circuits and Sys-tems for Video Techniques,1998.

[32]Elgammal A,Davis L S.Probabilistic Framework for Seg-menting People under Occlusion[C].Proc.of IEEE 8th In-ternational Conference on Computer Vision,2001.

[33]Senior A W,Hampapur A,Brown L M,et al.AppearanceModels for Occlusion Handling.in 2nd International Work-shop on Performance Evaluation of Tracking and Surveil-lance Systems,2001.

[34]Khan S,Shah M.Tracking People in Presence of Occlusion[C].in Asian Conference on Computer Vision,2000.

[35]Roh H K,Lee S W.Multiple People Tracking Using a Ap-pearance Model Based on Temporal Color[C].in Interna-tional Conference on Pattern Recognition,2000.

[36]Rosales R,Sclaroff S.Improved Tracking of Multiple Hu-mans with Trajectory Prediction and Occlusion Modeling[M].in Proc.IEEE Workshop on the Interpretation of Vis-ual Motion,1998.

[37]Dockstader S L,Tekalp A M.Tracking Multiple Objects inthe Presence of Articulated and Occluded Motion[M].inProc.Workshop Human Motion,2000.

[38]Isard M,Blake A.Condensation:Conditional Density Prop-agation for Visual Tracking.in International Journal ofComputer Vision,1998.

[39]Li P,Zhang T,Pece A E C.Visual Contour Tracking Basedon Particle Filters[M].in Image and VisionComputing,2003.

[40]Nummiaro K,Koller Meier E,Van Gool L.A Colorbased Particle Filter.in First International Workshop onGenerative Model based Vision,2002.

[41]Ok H W,Seo Y,Hong K S.Multiple Soccer Players Track-ing by Condensation with Occlusion Alarm Probability[M].International Workshop on Statistical Methods forVision Processing,2002.

[42]MacCormick J,Blake A.A Probabilistic Exclusion Principlefor Tracking Multiple Objects.in International Journal ofComputer Vision,2000.

[43]Ross Cutler,Larry S Davis.Robust Real Time PeriodicMotion Detection,Analysis,and Applications[J].IEEETransactions on Pattern Analysis and Machine Intelli-gence,2000,22(8).

[44]Liu Bo,Zhou Heqin.Using Object Classification to ImproveUrban Traffic Monitoring System.IEEE Int Conf.NeuralNetworks&Signal Processing,2003.

[45]Narasimhan S G,Nayar S K.Chromatic Framework for Vi-sion in Bad Weather[J].Proc.IEEE Computer Vision andPattern Recognition,2000:1 598 1 605.

[46]Kettnaker V,Zabih R.Bayesian Multi camera Surveillance[J].Proc.IEEE Computer Vision and Pattern Recognition,1999:253 259.

[47]Kelly P,Katkere A,Kuramura D,et al.An Architecture forMultiple Perspective Interactive Video.Proceedings of the3rd ACM International Conference on Multimedia,1995:201 212.

[48]Cai Q,Aggarwal J.Tracking Human Motion Using Multi-ple Cameras[C].Proc.International Conference on PatternRecognition,1996:68 72.

[49]Huang T,Russell S.Object Identification in a BayesianContext[J].Proceesings of IJCAI,1997:1 276 1 283.

[50]Hanna Pasula,Stuart J Russell,Michael Ostland,et al.Tracking Many Objects with Many Sensors[J].Proceed-ings of IJCAI,1999:1 160 1 171.

基本信息:

中图分类号:TP277

引用信息:

[1]杨建全,梁华,王成友.视频监控技术的发展与现状[J].现代电子技术,2006(21):84-88+91.

基金信息:

国家自然科学基金资助项目(60334010,60475029)

文档文件

引用

GB/T 7714-2015 格式引文
MLA格式引文
APA格式引文