Critical motion detection of nearby moving vehicles in a vision-based driver-assistance system

IEEE Transactions on Intelligent Transportation Systems

Volumn 10, Issue 1, 2009, Pages 70-82

  Cherng, Shen ^a   Fang, Chiung Yao ^b   Chen, Chia Pei ^c   Chen, Sei Wang ^b  

^a CHENG SHIU UNIVERSITY   (Taiwan)

^b NATIONAL TAIWAN NORMAL UNIVERSITY   (Taiwan)

^c CHUNGHWA TELECOM CO LTD   (Taiwan)

Author keywords

Assembly of adaptive resonance theory (ART) neural networks; Driver assistance system (DAS); Dynamic visual model (DVM); Fuzzy integral; Spatiotemporal attention (STA) neural network

Indexed keywords

ARTS COMPUTING; AUTOMOBILE DRIVERS; DIGITAL VOLTMETERS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MILITARY ELECTRONIC COUNTERMEASURES; RESONANCE; STORM SEWERS; SYNTHETIC APERTURES;

ADAPTIVE RESPONSE; COMPUTATIONAL MODELS; CONFIGURABILITY; DRIVER-ASSISTANCE SYSTEM (DAS); EPISODIC MEMORIES; FUZZY INTEGRAL; HIERARCHICAL PROCESSING; HUMAN VISUAL SYSTEMS; MOTION DETECTIONS; MOVING VEHICLES; SELECTIVE ATTENTIONS; SPATIOTEMPORAL ATTENTION (STA) NEURAL NETWORK; VISION-BASED;

FUZZY NEURAL NETWORKS;

EID: 61849163364     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2008.2011694     Document Type: Article

References (45)

1. T. Bachmann and S. Bujnoch. (2001). Connected Drive-Driver Assistance Systems of the Future. [Online], Available: http://195.30.248.73/ mercatorpark/pdf/ connectedDrive.pdf
2. M. Bertozzi and A. Broggi, "GOLD: A parallel real-time stereo vision system for generic obstacle and lane detection," IEEE Trans. Image Process., vol. 7, no. 1, pp. 62-81, Jan. 1998.
3. M. Bertozzi, A. Broggi, A. Fascioli, and S. Niclele, "Stereo vision-based vehicle detection," in Proc. IEEE Symp. Intell. Veh., Detroit, MI, 2000, pp. 39-44.
4. M. Bertozzi, A. Fascioli, and A. Broggi, "Performance analysis of a low-cost solution to vision-based obstacle detection," in Proc. IEEE Int. Conf. Intell. Transp. Syst., Tokyo, Japan, 1999, pp. 350-355.
5. G. A. Carpenter and S. Grossberg, Pattern Recognition by Self-Organizing Neural Networks. Cambridge, MA: MITPress, 1991, pp. 397-423.
6. H. Cheng, N. Zheng, X. Zhang, J. Qin, and H. van de Wetering, "Interactive road situation analysis for driver assistance and safety warning systems: Framework and algorithms," IEEE Trans. Intell. Transp. Syst., vol. 8, no. 1, pp. 157-167, Mar. 2007.
7. S. Denasi and G. Quaglia, "Obstacle detection using a deformable model of vehicles," in Proc. IEEE Symp. Intell. Veh., Tokyo, Japan. 2001, pp. 145-150.
8. M. P. Dubuisson, S. Lakshmanan, and A. K. Jain, "Vehicle segmentation and classification using deformable templates," IEEE Trans. Pattern Anal. Mach. Intell., vol. 18, no. 3, pp. 293-308, Mar. 1996.
9. A. Eidehall, J. Pohl, F. Gustafsson, and J. Ekmark, "Toward autonomous collision avoidance by steering," IEEE Trans. Intell. Transp. Syst., vol. 8, no. 1, pp. 84-94, Mar. 2007.
10. S. Ernst, C. Stiller, J. Goldbeck, and C. Roessig, "Camera calibration for lane and obstacle detection," in Proc. IEEE Int. Conf. Intell. Transp. Syst., 1999, pp. 356-361.
11. C. Y. Fang, C. S. Full, S. W. Chen, and P. S. Yen, "A road sign recognition system based on dynamic visual model," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recog., Madison, WI, 2003, vol. 1, pp. 750-755.
12. C. Y. Fang, H. L. Hsueh, and S. W. Chen, "Dangerous driving event analysis system by a cascaded fuzzy reasoning Petri net," in Proc. IEEE 9th Int. Conf. Intell. Transp. Syst., Toronto, ON, Canada, Sep. 17-20, 2006, pp. 337-342.
13. G. S. K. Fung, N. H. C. Yung, and G. K. H. Pang, "Vehicle shape approximation from motion for visual traffic surveillance," in Proc. IEEE Int. Conf. Intell. Transp. Syst., Oakland, CA, 2001, pp. 610-615.
14. D. Ghica, S. W. Lu, and X. Yuan, "Recognition of traffic signs by artificial neural network," in Proc. IEEE Int. Conf. Neural Netw., Perth, Australia, 1995, vol. 3, pp. 1444-1449.
15. R. L. Gregory, Eye and Brain, 3rd ed. New York: McGraw-Hill, 1978.
16. A. Hurlbert and T. Poggio, "Visual information: Do computers need attention," Nature, vol. 321, no. 6071, pp. 651-652, Jun. 1986.
17. T. Isogai, "On a measure of multivariate skewness and a test for multivariate normality," Ann. Inst. Stat. Math., vol. 34, no. 1, pp. 531-541, Dec. 1982.
18. K. Kaliyaperumal, S. Lakshmanan, and K. Kluge, "An algorithm for detecting roads and obstacles in radar images," IEEE Trans. Veh. Technol., vol. 50, no. 1, pp. 170-182, Jan. 2001.
19. T. Kato, Y. Ninomiya, and I. Kato, "An obstacle detection method by fusion of radar and motion stereo," IEEE Trans. Intell. Transp. Syst., vol. 3, no. 3, pp. 182-188, Sep. 2002.
20. L. A. Klein, Sensor Technologies and Data Requirements for ITS. Boston, MA: Artech House, 2001, pp. 306-307.
21. D. Koller, J. Weber, and J. Malik, "Robust multiple car tracking with occlusion reasoning," Univ. California at Berkeley, Berkeley, CA, Tech. Rep. UCB/CSD-93-780, 1993.
22. D. Koller, J. Weber, and J. Malik, "Towards real time visual based tracking in cluttered traffic scenes," in Proc. Intell. Veh. Symp., Paris, France, Oct. 24-26, 1994, pp. 201-206.
23. A. Kuehnle, "Symmetric-based vehicle location for AHS," in Proc. SPIE Transp. Sensors Controls: Collision Avoidance. Traffic Manag., ITS, Orlando, FL, 1998, vol. 2902, pp. 19-27.
24. S. Kyo, T. Koga, K. Sakurai, and S. Okazaki, "A robust vehicle detection and tracking system for wet weather conditions using the IMAP-vision image processing board," in Proc. IEEE Intell. Transp. Syst., Tokyo, Japan, 1999, pp. 423-428.
25. M. W. Levine and J. M. Shefner, Fundamentals of Sensation and Perception, 2nd ed. Pacific Grove, CA: Brooks/Cole, 1991, ch. 14.
26. M. Lützeler and E. D. Dickmanns, "Road recognition with MarVEye," in Proc. IEEE Symp. Intell. Veh., Stuttgart, Germany, 1998, pp. 341-346.
27. K. V. Mardia, "Measures of multivariate skewness and kurtosis with applications," Biometrika, vol. 57, no. 3, pp. 519-530, 1970.
28. C. Martindale, Cognitive Psychology: A Neural-Network Approach. Pacific Grove, CA: Brook/Cole, 1991.
29. Y. Matsushita, S. Kamijo, K. Ikeuchi, and M. Sakauchi, "Image processing based incident detection at intersections," in Proc. 4th Asian Conf. Comput. Vis., 2000, pp. 520-527.
30. D. Mitrovic, "Reliable method for driving events recognition," IEEE Trans. Intell. Transp. Syst., vol. 6, no. 2, pp. 198-205, Jun. 2005.
31. A. Polychronopoulos, M. Tsogas, A. J. Amditis, and L. Andreone, "Sensor fusion for predicting vehicles' path for collision avoidance systems," IEEE Trans. Intell. Transp. Syst., vol. 8, no. 3, pp. 549-562, Sep. 2007.
32. Y. Ruichek, "Multilevel- and neural-network-based stereo-matching method for real-time obstacle detection using linear cameras," IEEE Trans. Intell. Transp. Syst., vol. 6, no. 1, pp. 54-62, Mar. 2005.
33. M. Schraut, K. Naab, and T. Bachmann, "BMW's driver assistance concept for integrated longitudinal support," presented at the 7th Intelligent Transport Systems World Congr., Turin, Italy, 2000, Paper No. 2121.
34. R. Sekuler and R. Blake, Perception. New York: Knopf. 1985.
35. N. Shimomura, K. Fujimoto, T. Oki, and H. Muro, "Depth-based target segmentation for intelligent vehicles: Fusion of radar and binocular stereo," IEEE Trans. Intell. Transp. Syst., vol. 3, no. 3, pp. 196-202, Sep. 2002.
36. R. S. Snell, Clinical Neuroanatomy for Medical Students, 3rd ed. Boston, MA: Little, Brown, 1992.
37. M. Sugeno, "Fuzzy measure and fuzzy integrals: A survey," in Fuzzy Automatic and Decision Processes, M. M. Gupta, G. N. Saridis, and B. R. Gaines, Eds. Amsterdam, The Netherlands: North-Holland. 1977, pp. 89-102.
38. Z. Sun, G. Bebis, and R. Miller, "On-road vehicle detection using evolutionary Gabor filter optimization," IEEE Trans. Intell. Transp. Syst., vol. 6, no. 1, pp. 43-53, Jun. 2005.
39. P. Venhovens, J. Bernasch, J. Lowenau, H. Rieker, and M. Schraut, "The application of advanced vehicle navigation in BMW driver assistance systems," presented at the SAE Congr., Detroit, MI, 1999.
40. T. Viéville, E. Clergue, and P. E. D. S. Facao, "Computation of ego-motion and structure from visual and internal sensors using the vertical cue," in Proc. IEEE Int. Conf. Comput. Vis., Berlin, Germany, 1993, pp. 591-598.
41. Z. Wang and G. J. Klir, Fuzzy Measure Theory. New York: Plenum, 1992.
42. D. Willersinn and W. Enkelmann, "Robust obstacle detection and tracking by motion analysis," in Proc. IEEE Int. Conf. Intell. Transp. Syst., 1997, pp. 356-361.
43. M. Yamada, K. Ueda, I. Horiba, and N. Sugie, "Discrimination of the road condition toward understanding of vehicle driving environments," IEEE Trans. Intell. Transp. Syst., vol. 2, no. 1, pp. 26-34, Mar. 2001.
44. Y. Zhu, D. Comaniciu, M. Pellkofer, and T. Koehler, "Reliable detection of overtaking vehicles using robust information fusion," IEEE Trans. Intell. Transp. Syst., vol. 7, no. 4, pp. 401-414, Dec. 2006.
45. H. J. Zimmermann, Fuzzy Set Theory and Its Applications, 2nd ed. Boston, MA: Kluwer, 1991.