Incremental online object learning in a vehicular radar-vision fusion framework

IEEE Transactions on Intelligent Transportation Systems

Volumn 12, Issue 2, 2011, Pages 402-411

  Ji, Zhengping ^a   Luciw, Matthew ^b   Weng, Juyang ^c   Zeng, Shuqing ^d  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

^b DALLE MOLLE INSTITUTE FOR ARTIFICIAL INTELLIGENCE IDSIA   (Switzerland)

^c Michigan State University   (United States)

^d GENERAL MOTORS CORPORATION   (United States)

Author keywords

Biologically inspired neural network; intelligent vehicle system; object learning; sensor fusion; sparse coding

Indexed keywords

BIOLOGICALLY INSPIRED NEURAL NETWORKS; INTELLIGENT VEHICLE SYSTEM; OBJECT LEARNING; SENSOR FUSION; SPARSE CODING;

AUTOMOBILE DRIVERS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; LEARNING ALGORITHMS; NETWORK LAYERS; NEURAL NETWORKS; ONLINE SYSTEMS; RADAR SYSTEMS; UNSUPERVISED LEARNING; VIDEO CAMERAS;

E-LEARNING;

EID: 79958096006     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2010.2094188     Document Type: Conference Paper

References (31)

1. R. Bishop, "Intelligent vehicle R&D: A review and contrast of programs worldwide and emerging trends", Ann. Telecommun., vol. 60, no. 3/4, pp. 228-263, Mar./Apr. 2005. (Pubitemid 40749569)
2. C. Thorpe, M. H. Hebert, T. Kanade, and S. Shafer, "Vision and navigation for the Carnegie-Mellon Navlab", IEEE Trans. Pattern Anal. Mach. Intell., vol. 10, no. 3, pp. 362-373, May 1988.
3. B. Ulmer, "Vita II-Active collision avoidance in real traffic", in Proc. IEEE Intell. Vehicles Symp., 1994, pp. 1-6.
4. M. S. Darms, P. E. Rybski, C. Baker, and C. Urmson, "Obstacle detection and tracking for the urban challenge", IEEE Trans. Intell. Transp. Syst., vol. 10, no. 3, pp. 475-485, Sep. 2009.
5. 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.
6. J. Piao and M. McDonald, "Advanced driver assistance systems from autonomous to cooperative approach", Transp. Rev., vol. 28, no. 5, pp. 659-684, Sep. 2008.
7. T. Jochem and D. Langer, "Fusing radar and vision for detecting, classifying and avoiding roadway obstacles", in Proc. IEEE Intell. Vehicles Symp., 1996, pp. 333-338.
8. A. Gern, U. Franke, and P. Levi, "Advanced lane recognition-Fusing vision and radar", in Proc. IEEE Intell. Vehicles Symp., 2000, pp. 45-51. (Pubitemid 32135639)
9. U. Hofmann, A. Rieder, and E. D. Dickmanns, "EMS-vision: Application to hybrid adaptive cruise control", in Proc. IEEE Intell. Vehicles Symp., 2000, pp. 468-473. (Pubitemid 32135710)
10. U. Hofmann, A. Rieder, and E. D. Dickmanns, "Radar and vision data fusion for hybrid adaptive cruise control on highways", Mach. Vis. Appl., vol. 14, no. 1, pp. 42-49, Apr. 2003. (Pubitemid 40890135)
11. R. Grover, G. Brooker, and H. F. Durrant-Whyt, "A low level fusion of millimeter wave radar and night-vision imaging for enhanced characterization of a cluttered environment", in Proc. Australian Conf. Robot. Autom., 2001, pp. 14-15.
12. T. Kato, Y. Ninomiya, and I. Masaki, "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.
13. A. Sole, O. Mano, G. Stein, H. Kumon, Y. Tamatsu, and A. Shashua, "Solid or not solid: Vision for radar target validation", in Proc. IEEE Intell. Vehicles Symp., 2004, pp. 819-824.
14. G. Alessandretti, A. Broggi, and P. Cerri, "Vehicle and guard rail detection using radar and vision data fusion", IEEE Trans. Intell. Transp. Syst., vol. 8, no. 1, pp. 95-105, Mar. 2007. (Pubitemid 46376157)
15. U. Kadow, G. Schneider, and A. Vukotich, "Radar-vision based vehicle recognition with evolutionary optimized and boosted features", in Proc. IEEE Intell. Vehicles Symp., 2007, pp. 749-754.
16. M. Bertozzi, L. Bombini, P. Cerri, P. Medici, P. C. Antonello, and M. Miglietta, "Obstacle detection and classification fusing radar and vision", in Proc. IEEE Intell. Vehicles Symp., 2008, pp. 608-613.
17. S. Wu, S. Decker, P. Chang, T. Camus, and J. Eledath, "Collision sensing by stereo vision and radar sensor fusion", IEEE Trans. Intell. Transp. Syst., vol. 10, no. 4, pp. 606-614, Dec. 2009.
18. E. R. Kandel, J. H. Schwartz, and T. M. Jessell, Eds., Principles of Neural Science, 4th ed. New York: McGraw-Hill, 2000.
19. D. E. Sadava, H. C. Heller, G. H. Orians, W. K. Purves, and D. M. Hillis, Life, the Science of Biology, 8th ed. New York: Freeman, 2006.
20. E. Oja, "Principal components, minor components, and linear neural networks", Neural Netw., vol. 5, no. 6, pp. 927-935, Nov./Dec. 1992. (Pubitemid 23581250)
21. I. T. Jolliffe, Principal Component Analysis. New York: Springer-Verlag, 1986.
22. D. J. Field, "Relations between the statistics of natural images and the response properties of cortical cells", J. Opt. Soc. Amer. A, Opt. Image Sci., vol. 4, no. 12, pp. 2379-2394, Dec. 1987.
23. N. Zhang and J. Weng, "Sparse representation from a winner-take-all neural network", in Proc. Int. Joint Conf. Neural Netw., 2004, pp. 2209-2214. (Pubitemid 40006601)
24. A. Hyvarinen, "Survey on independent component analysis", Neural Comput. Surv., vol. 2, pp. 94-128, 1999.
25. J. Weng and M. Luciw, "Dually optimal neuronal layers: Lobe component analysis", IEEE Trans. Auton. Mental Develop., vol. 1, no. 1, pp. 68-85, May 2009.
26. D. H. Hubel and T. N. Wiesel, "Receptive fields of single neurons in the cat's striate cortex", J. Physiol., vol. 148, pp. 574-591, 1959.
27. B. A. Olshaushen and D. J. Field, "Emergence of simple-cell receptive field properties by learning a sparse code for natural images", Nature, vol. 381, no. 6583, pp. 607-609, Jun. 13, 1996. (Pubitemid 26177476)
28. J. Weng and M. Luciw, "Neuromorphic spatiotemporal processing", Michigan State Univ., East Lansing, MI, Tech. Rep. MSU-CSE-08-34, 2008.
29. G. Cauwenberghs and T. Poggio, "Incremental and decremental support vector machine learning", in Proc. Adv. Neural Inf. Process. Syst., Cambridge, MA, 2001, vol. 13, pp. 409-415.
30. J. Weng and W. Hwang, "Incremental hierarchical discriminant regression", IEEE Trans. Neural Netw., vol. 18, no. 2, pp. 397-415, Mar. 2007. (Pubitemid 46522565)
31. B. L. Milenova, J. S. Yarmus, and M. M. Campos, "SVM in oracle database 10g: Removing the barriers to widespread adoption of support vector machines", in Proc. 31st VLDB Conf., 2005, pp. 1152-1163. (Pubitemid 43991085)