Smart Cars and Smart Roads

This paper describes two projects applying computer vision to intelligent vehicle highway systems (IVHS). The first project has resulted in the development of a system for monitoring traffic scenes using video information. The objective is to estimate traffic parameters and detect quickly disruptive incidents. The second project is aimed at developing vision as a sensor technology for vehicle control using binocular stereopsis.

[1]  J. Mayhew,et al.  SWITCHER: a stereo algorithm for ground plane obstacle detection , 1990, Image Vis. Comput..

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

[3]  Hermann von Helmholtz,et al.  Treatise on Physiological Optics , 1962 .

[4]  Hans-Hellmut Nagel,et al.  Algorithmic characterization of vehicle trajectories from image sequences by motion verbs , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .

[6]  Jitendra Malik,et al.  An integrated stereo-based approach to automatic vehicle guidance , 1995, Proceedings of IEEE International Conference on Computer Vision.

[7]  Dean A. Pomerleau,et al.  Progress in neural network-based vision for autonomous robot driving , 1992, Proceedings of the Intelligent Vehicles `92 Symposium.

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

[9]  Surender K. Kenue Lanelok: Detection Of Lane Boundaries And Vehicle Tracking Using Image-Processing Techniques -Part II: Template Matching Algorithms , 1990, Other Conferences.

[10]  K. P. Karmann,et al.  Moving object recognition using an adaptive background memory , 1990 .

[11]  D. Koller,et al.  Towards robust automatic traffic scene analysis in real-time , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[12]  S. Chandrashekhar,et al.  Temporal analysis of stereo image sequences of traffic scenes , 1991, Vehicle Navigation and Information Systems Conference, 1991.

[13]  Larry H. Matthies,et al.  Stereo vision for planetary rovers: Stochastic modeling to near real-time implementation , 1991, Optics & Photonics.

[14]  Jitendra Malik,et al.  Robust Multiple Car Tracking with Occlusion Reasoning , 1994, ECCV.

[15]  Takeo Kanade,et al.  Vision and Navigation for the Carnegie-Mellon Navlab , 1987 .

[16]  Wilfried Enkelmann,et al.  Obstacle detection by evaluation of optical flow fields from image sequences , 1990, Image Vis. Comput..

[17]  Jitendra Malik,et al.  Automatic Symbolic Traffic Scene Analysis Using Belief Networks , 1994, AAAI.

[18]  Charles E. Thorpe,et al.  Representation and recovery of road geometry in YARF , 1992, Proceedings of the Intelligent Vehicles `92 Symposium.

[19]  G. D. Sullivan,et al.  Natural and artificial low-level seeing systems - Visual interpretation of known objects in constrained scenes , 1992 .

[20]  Daniel Raviv,et al.  A new approach to vision and control for road following , 1991, Proceedings of the IEEE Workshop on Visual Motion.

[21]  Y. Bar-Shalom Tracking and data association , 1988 .

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

[23]  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.

[24]  Ernst D. Dickmanns,et al.  Recursive 3-D Road and Relative Ego-State Recognition , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Larry S. Davis,et al.  Reconstruction of a road by local image matches and global 3D optimization , 1990, Proceedings., IEEE International Conference on Robotics and Automation.