Color model-based real-time learning for road following

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Volumn , Issue , 2006, Pages 939-944

  Tan, Ceryen ^a   Hong, Tsai ^a   Chang, Tommy ^a   Shneier, Michael ^a  

^a NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

Author keywords

Color models; Learning; Road following; Segmentation; Temporal fusion

Indexed keywords

ROAD FOLLOWING; TEMPORAL FUSION;

COLOR; MATHEMATICAL MODELS; REAL TIME SYSTEMS; ROADS AND STREETS;

LEARNING SYSTEMS;

EID: 37449025028     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Aufrere, R., Chapuis, R., Chausse, A fast and robust vision-based road following algorithm. Proc. IEEE Symposium on Intelligent Vehicles, Oct. 2000.
2. Aufrere, R., Marmoiton, F., Chapuis, R., Collange, F., and Derutin, J.P., Road Detection and Vehicle Tracking by Vision for Adaptive Cruise Control, The International Journal of Robotics Research, April 2001.
3. Broggi. A. and Berte, S., Vision-based road detection in automotive systems: a real-time expectation-driven approach, Journal of Artificial Intelligence Research, 1995
4. Beucher, S. and Bilodeau. M. Road segmentation and obstacle detection by a fast watershed transformation, Proc. Intelligent Vehicles '94 Symposium, 296-301, 1994.
5. Crisman, J.D., Thorpe, C.E., SCARF: A color vision system that tracks roads and intersections. IEEE Trans. Robotics and Automation, Feb. 1993.
6. Crisman, J. and Thorpe, C. UNSCARF, A color vision system for the detection of unstructured roads. Proc. International Conference on Robotics and Automation, 2496-2501, 1991.
7. Dickmanns. E. D., The development of machine vision for road vehicles in the last decade, Intelligent Vehicle Symposium, 2002.
8. Dickmanns, E. D. Vehicles capable of dynamic vision. International Joint Conference on Artificial Intelligence, 1577-1592, 1997
9. DeSourza, G. and Kak, A.,Vision for mobile robot navigation: a survey. IEEE Trans. Pattern Analysis and Machine Intelligence. Feb. 2002.
10. Födish, M. and Takeuchi. A., Adaptive real-time road detection using neural networks, Proc. 7th International IEEE Conference on Intelligent Transportation Systems. Oct. 2004.
11. He. Y., Wang, H., Zhang. B., Color-based road detection in urban traffic scenes, IEEE Trans. Intelligent Transportation Systems. Dec. 2004.
12. Hong, T., Rasmussen. C. and Shneier, M., road detection and tracking for autonomous mobile robots, Proc. SPIE 4715, April 2002.
13. Jochem, T. and Baluja, S., A massively parallel road follower. Computer Architecture for Machine Perception, Dec. 1993.
14. Kristensen, D.. Autonomous road following - a study of methods for tracking unmarked roads in image sequences, Master's degree project, Stockholm, Sweden . 2004.
15. Kosecks. R., Blasi, C.J., Taylor. J., Malik. J., A comparative study of vision-based lateral control strategies for autonomous high-way driving, IEEE International Conference on Robotics And Automation, 1998.
16. Kuan, D., Phipps, G., Hsueh, A., autonomous robotic vehicle road following, IEEE Trans. Pattern Analysis and Machine Intelligence, Sept. 1988.
17. Lin, X. and Chen, S., Color image segmentation using modified his system for road following, Proc. 1991 IEEE International Conference on Robotics and Automation, 1991.
18. Pomerleau. D. RALPH: Rapidly adapting lateral position handler. Proc. IEEE Intelligent Vehicles Symposium, 506-511, 1995
19. Pomerleau, D.. ALVINN: An autonomous Land Vehicle in A Neural Network, Technical Report, CM-CS-89-107, Carnegie Mellon, 1989.
20. Rotaru. C., Graf, T., Zhang, J., Extracting road features from color images using a cognitive approach, IEEE Intelligent Vehicle Symposium, 2004.
21. Schneiderman, H. and Nashman, M., A discriminating feature tracker for vision-based autonomous driving. IEEE Trans. Robotics and Automation, vol. 10, no. 6, 1994.
22. Thorpe, C., Hebert, M. H., Kanade, T., Shafer. S.A., vision and navigation for Carnegie-Mellon Navlab, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 10, May. 1988.
23. Zhang, J. and Nagel, H., Texture-based segmentation of road images, Intelligent Vehicle symposium, Oct. 1994.