A methodology for precise camera calibration for data collection applications in urban traffic scenes

Camera calibration is a necessary step in all video analysis applications to recover the real-world positions of concerned road users. Camera calibration can be performed based on feature correspondences between the real-world space and image space. In urban traffic scenes, the field of view may be too limited or video camera may not be accessible to allow reliable calibration based on vanishing points. A review of the current methods for camera calibration reveals little attention to these practical challenges that arise when studying urban intersections to support applications in traffic engineering. This study presents the development details of a robust camera calibration approach based on integrating a collection of geometric information found in urban traffic scenes in a consistent optimization framework. The developed approach was tested on six datasets obtained from urban intersections in British Columbia, California, and Kentucky. The results clearly demonstrated the robustness of the proposed ap...

[1]  Shi Peng-fei,et al.  Efficient method for camera calibration in traffic scenes , 2004 .

[2]  Dariu Gavrila,et al.  Monocular Pedestrian Detection: Survey and Experiments , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Flávio Cunto,et al.  Calibration and validation of simulated vehicle safety performance at signalized intersections. , 2008, Accident; analysis and prevention.

[4]  Peter F. Sturm,et al.  Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Tarek Sayed,et al.  Application of Computer Vision to Diagnosis of Pedestrian Safety Issues , 2013 .

[6]  C. Fraser,et al.  Digital camera calibration methods: Considerations and comparisons , 2006 .

[7]  Paul R. Cohen,et al.  Camera Calibration with Distortion Models and Accuracy Evaluation , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Yunfeng Ai,et al.  On Automatic and Dynamic Camera Calibration based on Traffic Visual Surveillance , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[9]  Wayne A Sarasua,et al.  Automatic Camera Calibration Using Pattern Detection for Vision-Based Speed Sensing , 2008 .

[10]  Tarek Sayed,et al.  Classifying Road Users in Urban Scenes Using Movement Patterns , 2012 .

[11]  Catherine Morency,et al.  Estimation of Frequency and Length of Pedestrian Stride in Urban Environments with Video Sensors , 2011 .

[12]  Osama Masoud,et al.  Using geometric primitives to calibrate traffic scenes , 2007 .

[13]  Daniel J. Dailey,et al.  Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation , 2003, IEEE Trans. Intell. Transp. Syst..

[14]  Tarek Sayed,et al.  Automated Analysis and Validation of Right-Turn Merging Behavior , 2015 .

[15]  Geoffrey D. Sullivan,et al.  A Simple, Intuitive Camera Calibration Tool for Natural Images , 1994, BMVC.

[16]  Tarek Sayed,et al.  Use of Drivers’ Jerk Profiles in Computer Vision–Based Traffic Safety Evaluations , 2014 .

[17]  Tarek Sayed,et al.  Use of Spatiotemporal Parameters of Gait for Automated Classification of Pedestrian Gender and Age , 2013 .

[18]  Wayne A Sarasua,et al.  Real-Time Detection and Tracking of Vehicle Base Fronts for Measuring Traffic Counts and Speeds on Highways , 2007 .

[19]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[20]  Tarek Sayed,et al.  The use of gait parameters to evaluate pedestrian behavior at scramble phase signalized intersections , 2015 .

[21]  Tarek Sayed,et al.  Automated Collection of Pedestrian Data through Computer Vision Techniques , 2012 .

[22]  Jianping Wu,et al.  Horizontal Roadway Curvature Computation Algorithm Using Vision Technology , 2010, Comput. Aided Civ. Infrastructure Eng..

[23]  Tarek Sayed,et al.  Large-Scale Automated Analysis of Vehicle Interactions and Collisions , 2010 .

[24]  Tarek Sayed,et al.  Computer Vision Techniques for the Automated Collection of Cyclist Data , 2013 .

[25]  T. Sayed,et al.  Automated Collection of Pedestrian Data Using Computer Vision Techniques , 2009 .

[26]  Songde Ma,et al.  Implicit and Explicit Camera Calibration: Theory and Experiments , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Tarek Sayed,et al.  Automated Safety Diagnosis of Vehicle–Bicycle Interactions Using Computer Vision Analysis , 2013 .

[28]  Tarek Sayed,et al.  Automated Analysis of Pedestrian–Vehicle Conflicts , 2010 .

[29]  Tarek Sayed,et al.  Automated Analysis of Pedestrian Crossing Speed Behavior at Scramble-phase Signalized Intersections Using Computer Vision Techniques , 2014 .

[30]  Tarek Sayed,et al.  Probabilistic Collision Prediction for Vision-Based Automated Road Safety Analysis , 2007, 2007 IEEE Intelligent Transportation Systems Conference.

[31]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Tarek Sayed,et al.  Computer Vision Techniques to Collect Helmet-Wearing Data on Cyclists , 2014 .

[33]  Yasser Hassan,et al.  Automated measuring of cyclist – motor vehicle post encroachment time at signalized intersections , 2014 .

[34]  Tarek Sayed,et al.  Using automated walking gait analysis for the identification of pedestrian attributes , 2014 .

[35]  Yao-Jan Wu,et al.  Video-Based Monitoring of Pedestrian Movements at Signalized Intersections , 2008 .

[36]  S. Bougnoux,et al.  From projective to Euclidean space under any practical situation, a criticism of self-calibration , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[37]  Tarek Sayed,et al.  Automated Detection of Spatial Traffic Violations through use of Video Sensors , 2011 .

[38]  Zhengyou Zhang Estimating Motion and Structure from Correspondences of Line Segments between Two Perspective Images , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[39]  Radu Horaud,et al.  Object pose from 2-D to 3-D point and line correspondences , 1995, International Journal of Computer Vision.

[40]  Loong Fah Cheong,et al.  Automatic camera calibration of broadcast tennis video with applications to 3D virtual content insertion and ball detection and tracking , 2009, Comput. Vis. Image Underst..

[41]  Tarek Sayed,et al.  A framework for automated road-users classification using movement trajectories , 2013 .

[42]  B. Caprile,et al.  Using vanishing points for camera calibration , 1990, International Journal of Computer Vision.

[43]  Robert J. Woodham,et al.  Combining Line and Point Correspondences for Homography Estimation , 2008, ISVC.

[44]  Tarek Sayed,et al.  Automated Analysis of Pedestrian–Vehicle Conflicts Using Video Data , 2009 .

[45]  Tarek Sayed,et al.  Automated Analysis of Pedestrians’ Nonconforming Behavior and Data Collection at an Urban Crossing , 2014 .