Video processing techniques for traffic flow monitoring: A survey

Video-based traffic flow monitoring is a fast emerging field based on the continuous development of computer vision. A survey of the state-of-the-art video processing techniques in traffic flow monitoring is presented in this paper. Firstly, vehicle detection is the first step of video processing and detection methods are classified into background modeling based methods and non-background modeling based methods. In particular, nighttime detection is more challenging due to bad illumination and sensitivity to light. Then tracking techniques, including 3D model-based, region-based, active contour-based and feature-based tracking, are presented. A variety of algorithms including MeanShift algorithm, Kalman Filter and Particle Filter are applied in tracking process. In addition, shadow detection and vehicles occlusion bring much trouble into vehicle detection, tracking and so on. Based on the aforementioned video processing techniques, discussion on behavior understanding including traffic incident detection is carried out. Finally, key challenges in traffic flow monitoring are discussed.

[1]  Ramakant Nevatia,et al.  Event Detection and Analysis from Video Streams , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Shuming Tang,et al.  A survey of vision-based automatic incident detection technology , 2005, IEEE International Conference on Vehicular Electronics and Safety, 2005..

[3]  M. Elif Karsligil,et al.  Severity detection of traffic accidents at intersections based on vehicle motion analysis and multiphase linear regression , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[4]  Akihiro Takeuchi,et al.  On-road vehicle tracking using deformable object model and particle filter with integrated likelihoods , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[5]  Jitendra Malik,et al.  A real-time computer vision system for measuring traffic parameters , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Mohan M. Trivedi,et al.  Distributed video networks for incident detection and management , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[7]  Sergio A. Velastin,et al.  A Review of Computer Vision Techniques for the Analysis of Urban Traffic , 2011, IEEE Transactions on Intelligent Transportation Systems.

[8]  Peter Schallauer,et al.  Multimodal highway monitoring for robust incident detection , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[9]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Massimo Piccardi,et al.  Background subtraction techniques: a review , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[11]  Chien-Cheng Tseng,et al.  Image-based vehicle tracking and classification on the highway , 2010, The 2010 International Conference on Green Circuits and Systems.

[12]  M. Kilger,et al.  A shadow handler in a video-based real-time traffic monitoring system , 1992, [1992] Proceedings IEEE Workshop on Applications of Computer Vision.

[13]  Yoshiaki Shirai,et al.  Surveillance system based on spatio-temporal information , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[14]  He Zhao,et al.  Traffic incident classification at intersections based on image sequences by HMM/SVM classifiers , 2010, Multimedia Tools and Applications.

[15]  Sergio L. Toral Marín,et al.  A shadow removal algorithm for vehicle detection based on reflectance ratio and edge density , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[16]  Manli Zhou,et al.  Robust vehicle tracking based on Scale Invariant Feature Transform , 2008, 2008 International Conference on Information and Automation.

[17]  Larry S. Davis,et al.  A Robust Background Subtraction and Shadow Detection , 1999 .

[18]  M. Elif Karsligil,et al.  Video-based traffic accident analysis at intersections using partial vehicle trajectories , 2010, 2010 IEEE International Conference on Image Processing.

[19]  Martin Litzenberger,et al.  Night-time vehicle classification with an embedded, vision system , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[20]  Tieniu Tan,et al.  Traffic accident prediction using vehicle tracking and trajectory analysis , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[21]  Zhang Junping,et al.  Method of removing moving shadow based on texture , 2008, 2008 Chinese Control and Decision Conference.

[22]  Wang Liang,et al.  A Survey of Visual Analysis of Human Motion , 2002 .

[23]  Sei-Wang Chen,et al.  Shadow detection and removal for traffic images , 2004, IEEE International Conference on Networking, Sensing and Control, 2004.

[24]  Xiaohui Wang,et al.  A Detection and Tracing Algorithm of Moving Vehicles , 2007, 2007 2nd International Conference on Pervasive Computing and Applications.

[25]  Narciso García,et al.  An adaptive, real-time, traffic monitoring system , 2009, Machine Vision and Applications.

[26]  M. Kilger,et al.  Video-based traffic monitoring , 1992 .

[27]  Chengcui Zhang,et al.  Learning-based spatio-temporal vehicle tracking and indexing for transportation multimedia database systems , 2003, IEEE Trans. Intell. Transp. Syst..

[28]  Weihong Wang,et al.  A Two-Layer Night-Time Vehicle Detector , 2009, 2009 Digital Image Computing: Techniques and Applications.

[29]  Mubarak Shah,et al.  Tracking and Object Classification for Automated Surveillance , 2002, ECCV.

[30]  Paola Mello,et al.  Image analysis and rule-based reasoning for a traffic monitoring system , 2000, IEEE Trans. Intell. Transp. Syst..

[31]  Kostia Robert.  Night-Time Traffic Surveillance: A Robust Framework for Multi-vehicle Detection, Classification and Tracking , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.

[32]  Azeddine Beghdadi,et al.  Vehicle Tracking by non-Drifting Mean-shift using Projective Kalman Filter , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[33]  W. Eric L. Grimson,et al.  Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[34]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[35]  Rita Cucchiara,et al.  Improving shadow suppression in moving object detection with HSV color information , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[36]  Azeddine Beghdadi,et al.  Vehicle Tracking Using Projective Particle Filter , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.

[37]  Bing-Fei Wu,et al.  Real-time vision-based multiple vehicle detection and tracking for nighttime traffic surveillance , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[38]  Kuntal Sengupta,et al.  Framework for real-time behavior interpretation from traffic video , 2005, IEEE Transactions on Intelligent Transportation Systems.

[39]  Xiaobo Lu,et al.  An Accurate Shadow Removal Method for Vehicle Tracking , 2010, 2010 International Conference on Artificial Intelligence and Computational Intelligence.

[40]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[41]  A. Lai,et al.  A fast and accurate scoreboard algorithm for estimating stationary backgrounds in an image sequence , 1998, ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187).

[42]  Reinhard Koch,et al.  A Color Similarity Measure for Robust Shadow Removal in Real Time , 2003, VMV.

[43]  Osama Masoud,et al.  A vision-based approach to collision prediction at traffic intersections , 2005, IEEE Transactions on Intelligent Transportation Systems.

[44]  Katsushi Ikeuchi,et al.  Traffic monitoring and accident detection at intersections , 2000, IEEE Trans. Intell. Transp. Syst..

[45]  Luo Di,et al.  Texture Analysis for Shadow Removing and Tracking of Vehicle in Traffic Monitoring System , 2008, 2008 International Symposium on Intelligent Information Technology Application Workshops.

[46]  M. Elif Karsligil,et al.  Video-based traffic accident analysis at intersection using partial vehicle trajectories , 2010, CIVR.

[47]  Zhaoquan Cai,et al.  Automatic Detection of Vehicle Activities Based on Particle Filter Tracking , 2009 .

[48]  Hironobu Fujiyoshi,et al.  Moving target classification and tracking from real-time video , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[49]  Larry S. Davis,et al.  Real-time foreground-background segmentation using codebook model , 2005, Real Time Imaging.

[50]  Olaf Munkelt,et al.  Adaptive Background Estimation and Foreground Detection using Kalman-Filtering , 1995 .

[51]  Kostia Robert,et al.  Video-based traffic monitoring at day and night vehicle features detection tracking , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[52]  Bing-Fei Wu,et al.  A real-time multiple-vehicle detection and tracking system with prior occlusion detection and resolution , 2005, Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005..

[53]  Rangasami L. Kashyap,et al.  Identifying Overlapped Objects for Video Indexing and Modeling in Multimedia Database Systems , 2001, Int. J. Artif. Intell. Tools.

[54]  M. V. Lamar,et al.  A new approach to multiple vehicle tracking in intersections using harris corners and adaptive background subtraction , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[55]  Osama Masoud,et al.  A collision prediction system for traffic intersections , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[56]  P. G. Michalopoulos,et al.  Vehicle detection video through image processing: the Autoscope system , 1991 .