Adaptive Road Recognition and Ego-state Tracking in the Presence of Obstacles

International Journal of Computer Vision

Volumn 28, Issue 1, 1998, Pages 5-26

  Kasprzak, Wlodzimierz ^a,b   Niemann, Heinrich ^a  

^a Bayerisches Forschungszentrum fur wissensbasierte Systeme FORWISS   (Germany)

^b WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Adaptive recognition; Competitive hypotheses; Image sequences; Kalman filter; Moving camera; Road stripes; Vanishing point

Indexed keywords

ADAPTIVE SYSTEMS; COLLISION AVOIDANCE; KALMAN FILTERING; ROADS AND STREETS; CAMERAS; COMPUTER VISION; NEURAL NETWORKS; PARAMETER ESTIMATION; REAL TIME SYSTEMS; VELOCITY MEASUREMENT;

ADAPTIVE RECOGNITION; EGO STATE TRACKING; VANISHING POINT TRACKING;

COMPUTER VISION; IMAGE ANALYSIS;

ADAPTIVE RECOGNITION; COMPETITIVE HYPOTHESES; IMAGE SEQUENCES; MOVING CAMERAS; ROAD STRIPES; VANISHING POINTS;

EID: 0032097636     PISSN: 09205691     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008025713790     Document Type: Article

References (23)

1. Brammer, K. and Siffling, G. 1975. Kalman-Bucy-Filter - Deterministische Beobachtung und Stochastische Filterung. R. Oldenburg-Verlag: München, Wien.
2. Chen, X., Dagless, E., Zhang, S., and Thomas, B. 1993. A real-time plan view method for following bending roads. IEEE Symposium on Intelligent Vehicles, Tokyo, Japan, pp. 219-224.
3. Dickmanns, E. and Mysliwetz, B. 1992. Recursive 3D road and relative ego-state recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2):199-214.
4. Fujimori, T. and Kanade, T. 1990. An approach to knowledge-based interpretation of outdoor natural color road scenes. In Vision and Navigation: The Carnegie Mellon Navlab., C. Thorpe (Ed.), Chapt. 4, Kluwer Academic Publishers.
5. Gennery, D.-B. 1992. Visual tracking of known three-dimensional objects. International Journal of Computer Vision, 7:243-270.
6. Graefe, V 1993. Vision for intelligent road vehicles. Proceedings, IEEE Symposium on Intelligent Vehicles, Tokyo, pp. 135-140.
7. Jochem, T.M. 1996. Vision based tactical driving. Ph.D. dissertation, CMU-RI-TR-96-14, Carnegie Mellon University.
8. Kasprzak, W. 1995. Ground plane object tracking under egomotion. International Archives of Photogrammetry and Remote Sensing, 30(Part 5W1):208-213.
9. Kasprzak, W., Niemann, H., and Wetzel, D. 1994. Adaptive road parameter estimation in monocular image sequences. In British Machine Vision Conference, E. Hancock, (Ed.), BMVA Press: Sheffield, vol. 2, pp. 691-700.
10. Kasprzak, W. and Niemann, H. 1995. Moving segment detection in monocular image sequences under egomotion. Signal Processing VII: Theories and Applications, EURASIP: Lausanne, pp. 708-711.
11. Kluge, K. and Thorpe, C. 1990. Explicite models for robot road following. In Vision and Navigation: The Carnegie Mellon Navlab., C. Thorpe (Ed.), Chapt. 3, Kluwer Academic Publishers.
12. Koller, D. 1992. Detektion, Verfolgung und Klassifikation bewegter Objekte in monokularen Eidfolgen am Beispiel von Strassenverkehrsszenen. Infix: Sankt Augustin.
13. Koller, D., Daniilidis, K., and Nagel, H.-H. 1993. Model-based object tracking in monocular image sequences of road traffic scenes. International Journal of Computer Vision, 10(3):257-281.
14. Masaki, I. 1992. Vision-based Vehicle Guidance. Springer: New York, Berlin, Heidelberg.
15. Maurer, M., Behringer, R., Thomanek, F., and Dickmanns, E.D. 1996. A compact vision system for road vehicle guidance. 13th International Conference on Pattern Recognition, Vienna.
16. Morgan, A., Dagless, E., Milford, D., and Thomas, B. 1990. Road edge tracking for robot road following: A real-time implementation. Image and Vision Computing, 8(3):233-240.
17. Polk, A. and Jain, R. 1992. A parallel architecture for curvaturebased road scene classification. In Vision-Based Vehicle Guidance, I. Masaki (Ed.), Springer: New York, pp. 284-299.
18. Pomerleau, D.A. 1991. Rapidly adapting artificial neural networks for autonomous navigation. In Advances in Neural Information Processing Systems, 3, R.P. Lippmann, J.E. Moody, and D.S. Touretzky (Eds.), Morgan Kaufmann Publ.: San Mateo, CA, pp. 429-435.
19. Pomerleau, D.A. 1993. Neural networks for intelligent vehicles. In Proceedings of IEEE Conf. on Intelligent Vehicles, IEEE Publ., pp. 19-24.
20. Pomerleau, D.A. 1995. RALPH: Rapidly adapting lateral position handler. IEEE Symposium on Intelligent Vehicles, Detroit: Michigan, USA.
21. Schaaser, L. and Thomas, B. 1992. Finding road lane boundaries for vision-guided vehicle navigation. In Vision-Based Vehicle Guidance, I. Masaki (Ed.), Springer: New York, pp. 239-254.
22. Wetzel, D., Niemann, H., and Richter, S. 1994. A robust cognitive approach to traffic scene analysis. In Proceedings of the Second IEEE Workshop on Applications of Computer Vision, IEEE Computer Society Press: Los Alamitos, CA, USA, pp. 65-72.
23. Wu, J., Rink, R., Caelli, T., and Gourishankar, V. 1988. Recovery of the 3D location and motion of a rigid object through camera image. International Journal of Computer Vision, 3:373-394.