Mobile Active‐Vision Traffic Surveillance System for Urban Networks

This article discusses the development of a mobile bus-mounted machine vision system for transit and traffic monitoring in urban corridors, as required by intelligent transportation systems. In contrast to earlier machine vision technologies used for traffic management, which rely mainly on fixed-point detection and simpler algorithms to detect certain traffic characteristics, the new proposed approach makes use of a recent trend in com- puter vision research; namely, the active vision paradigm. Active vision systems have mechanisms that can actively control camera parameters such as orientation, focus, zoom, and vergence in response to the requirements of the task and external stimuli. Mounting active vision systems on buses will have the advantage of providing real-time feedback of the current traffic conditions, while possess- ing the intelligence and visual skills that allow them to interact with a rapidly changing dynamic environment, such as moving traffic and continuously changing image background.

[1]  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.

[2]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Richard A. Young,et al.  SIMULATION OF HUMAN RETINAL FUNCTION WITH THE GAUSSIAN DERIVATIVE MODEL. , 1986 .

[4]  A. El-Rabbany,et al.  Mobile vision-based vehicle tracking and traffic control , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[5]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[6]  Patrick Bouthemy,et al.  Estimation of time-to-collision maps from first order motion models and normal flows , 1992, [1992] Proceedings. 11th IAPR International Conference on Pattern Recognition.

[7]  Alan C. Bovik,et al.  Stereo disparity from multiscale processing of local image phase , 1995, Proceedings of International Symposium on Computer Vision - ISCV.

[8]  William T. Freeman,et al.  Presented at: 2nd Annual IEEE International Conference on Image , 1995 .

[9]  J. Gibson The Ecological Approach to Visual Perception , 1979 .

[10]  Martin Jägersand,et al.  Saliency Maps and Attention Selection in Scale and Spatial Coordinates: An Information Theoretic Approach , 1995, ICCV.

[11]  Chung-Lin Huang,et al.  Motion estimation method using a 3D steerable filter , 1995, Image Vis. Comput..

[12]  D. Ballard,et al.  Object recognition using steerable filters at multiple scales , 1993, [1993] Proceedings IEEE Workshop on Qualitative Vision.

[13]  David J. Fleet,et al.  Phase-based disparity measurement , 1991, CVGIP Image Underst..

[14]  P W Shuldiner PRACTITIONER'S FORUM: VIDEO TECHNOLOGY IN TRAFFIC ENGINEERING AND TRANSPORTATION PLANNING , 1999 .

[15]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[16]  Demetri Terzopoulos,et al.  Stereo and color analysis for dynamic obstacle avoidance , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[17]  Demetri Terzopoulos,et al.  Motion and Color Analysis for Animat Perception , 1996, AAAI/IAAI, Vol. 2.

[18]  Michal Irani,et al.  Image sequence enhancement using multiple motions analysis , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[20]  P. Anandan,et al.  A computational framework and an algorithm for the measurement of visual motion , 1987, International Journal of Computer Vision.

[21]  Jitendra Malik,et al.  Computational framework for determining stereo correspondence from a set of linear spatial filters , 1992, Image Vis. Comput..

[22]  Demetri Terzopoulos,et al.  Animat vision: Active vision in artificial animals , 1995, Proceedings of IEEE International Conference on Computer Vision.

[23]  K. Langley,et al.  Vertical and Horizontal Disparities from Phase , 1990, ECCV.

[24]  Paul W. Shuldiner PRACTITIONER'S FORUM , 1999 .

[25]  V. Torre,et al.  Optic Flow and Autonomous Navigation , 1995, Perception.

[26]  K.D. Baker,et al.  Performance assessment of model-based tracking , 1992, [1992] Proceedings IEEE Workshop on Applications of Computer Vision.

[27]  Kai-Yeung Siu,et al.  Vehicle detection and tracking for freeway traffic monitoring , 1994, Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers.

[28]  T. Sanger,et al.  Stereo disparity computation using Gabor filters , 1988, Biological Cybernetics.

[29]  Gianni Conte,et al.  Automatic Vehicle Guidance: the Experience of the ARGO Autonomous Vehicle , 1999 .

[30]  Peter J. Burt,et al.  Object tracking with a moving camera , 1989, [1989] Proceedings. Workshop on Visual Motion.

[31]  R. Hingorani,et al.  OBJECT TRACKING WITH A MOVING CAMERA An Application of Dynaiiiic Motion Analysis , 1989 .

[32]  D Marr,et al.  A computational theory of human stereo vision. , 1979, Proceedings of the Royal Society of London. Series B, Biological sciences.

[33]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[34]  Hans-Hellmut Nagel,et al.  Model-based object tracking in monocular image sequences of road traffic scenes , 1993, International Journal of Computer 11263on.

[35]  John K. Tsotsos,et al.  Active stereo vision and cyclotorsion , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[36]  Michal Irani,et al.  Recovery of ego-motion using image stabilization , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

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

[38]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[39]  Jitendra Malik,et al.  A Computational Framework for Determining Stereo Correspondence from a Set of Linear Spatial Filters , 1991, ECCV.