Vehicle detection by independent parts for urban driver assistance

IEEE Transactions on Intelligent Transportation Systems

Volumn 14, Issue 4, 2013, Pages 1597-1608

  Sivaraman, Sayanan ^a   Trivedi, Mohan Manubhai ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Active learning; Active safety; Computer vision; Detection by parts; Machine learning; Occlusions; Vehicle detection

Indexed keywords

ACTIVE LEARNING; ACTIVE SAFETY; DETECTION BY PARTS; OCCLUSIONS; VEHICLE DETECTION;

AUTOMOBILE DRIVERS; COMPUTER VISION; LEARNING SYSTEMS;

VEHICLES;

EID: 84890435558     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2013.2264314     Document Type: Article

References (46)

1. Traffic Safety Facts, Department of Transportation-National Highway Traffic Safety Administration, Washington, DC, USA, 2011.
2. M. M. Trivedi and S. Y. Cheng, "Holistic sensing and active displays for intelligent driver support systems," IEEE Comput., vol. 40, no. 5, pp. 60-68, May 2007.
3. Z. Sun, G. Bebis, and R. Miller, "On-road vehicle detection: A review," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 5, pp. 694-711, May 2006.
4. S. Sivaraman and M. M. Trivedi, "Active learning for on-road vehicle detection: A comparative study," Mach. Vis. Appl., Special Issue Car Navig. Veh. Syst., Dec. 2011.
5. A. Jazayeri, H. Cai, J. Y. Zheng, and M. Tuceryan, "Vehicle detection and tracking in car video based on motion model," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 2, pp. 583-595, Jun. 2011.
6. S. Sivaraman and M. Trivedi, "Integrated lane and vehicle detection, localization, and tracking: A synergistic approach," IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, pp. 906-917, Jun. 2013.
7. W.-C. Chang and C.-W. Cho, "Online boosting for vehicle detection," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 40, no. 3, pp. 892-902, Jun. 2010.
8. R. O'Malley, E. Jones, and M. Glavin, "Rear-lamp vehicle detection and tracking in low-exposure color video for night conditions," IEEE Trans. Intell. Transp. Syst., vol. 11, no. 2, pp. 453-462, Jun. 2010.
9. S. Sivaraman and M. M. Trivedi, "A general active learning framework for on-road vehicle recognition and tracking," IEEE Trans. Intell Transp. Syst., vol. 11, no. 2, pp. 267-276, Jun. 2010.
10. B.-F. Lin, Y.-M. Chan, L.-C. Fu, P.-Y. Hsiao, L.-A. Chuang, S.-S. Huang, and M.-F. Lo, "Integrating appearance and edge features for sedan vehicle detection in the blind-spot area," IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp. 737-747, Jun. 2012.
11. H. Tehrani Niknejad, A. Takeuchi, S. Mita, and D. McAllester, "On-road multivehicle tracking using deformable object model and particle filter with improved likelihood estimation," IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp. 748-758, Jun. 2012.
12. J. C. Rubio, J. Serrat, A. M. Lopez, and D. Ponsa, "Multiple-target tracking for intelligent headlights control," IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp. 594-605, Jun. 2012.
13. S. Sivaraman and M. M. Trivedi, "Real-time vehicle detection using parts at intersections," in Proc. IEEE Intell. Transp. Syst. Conf., 2012, pp. 1519-1524.
14. F. Garcia, P. Cerri, A. Broggi, A. de la Escalera, and J.M. Armingol, "Data fusion for overtaking vehicle detection based on radar and optical flow," in Proc. IEEE IV Symp., Jun. 2012, pp. 494-499.
15. P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan, "Object detection with discriminatively trained part based models," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 9, pp. 1627-1645, Sep. 2010.
16. B. Wu and R. Nevatia, "Detection and segmentation of multiple, partially occluded objects by grouping, merging, assigning part detection responses," Int. J. Comput. Vis., vol. 82, no. 2, pp. 185-204, Apr. 2009.
17. D. Tosato, M. Farenzena, M. Cristani, and V. Murino, "Part-based human detection on Riemannian manifolds," in Proc. IEEE Int. Conf. Image Process., 2010, pp. 3469-3472.
18. O. Tuzel, F. Porikli, and P. Meer, "Pedestrian detection via classification on Riemannian manifolds," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 10, pp. 1713-1727, Oct. 2008.
19. Z. Lin, G. Hua, and L. Davis, "Multiple instance feature for robust partbased object detection," in Proc. IEEE Comput. Vis. Pattern Recognit., 2009, pp. 405-412.
20. W.-C. Chang and C.-W. Cho, "Real-time side vehicle tracking using partsbased boosting," in Proc. IEEE Int. Conf. SMC, 2008, pp. 3370-3375.
21. A. Barth and U. Franke, "Tracking oncoming and turning vehicles at intersections," in Proc. IEEE Intell. Transp. Syst. Conf., 2010, pp. 861-868.
22. H. Badino, R. Mester, J. Wolfgang, and U. Franke, "Free space computation using stochastic occupancy grids and dynamic programming," in Proc. ICCV Workshop Dyn. Vis., 2007, pp. 1-12.
23. S. Sivaraman and M. M. Trivedi, "Combining monocular and stereovision for real-time vehicle ranging and tracking on multilane highways," in Proc. IEEE Intell. Transp. Syst. Conf., 2011, pp. 1249-1254.
24. R. Danescu, F. Oniga, and S. Nedevschi, "Modeling and tracking the driving environment with a particle-based occupancy grid," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1331-1342, Dec. 2011.
25. C. Huang and R. Nevatia, "High performance object detection by collaborative learning of joint ranking of granules features," in Proc. Comput. Vis. Pattern Recognit., 2010, pp. 41-48.
26. D. Tosato, M. Farenzena, M. Cistani, and V. Murino, "A re-evaluation of pedestrian detection on Riemannian manifolds," in Proc. Int. Conf. Pattern Recognit., 2010, pp. 3308-3311.
27. P. Felzenszwalb, R. Girshick, and D. McAllester, "Cascade object detection with deformable part models," in Proc. IEEE Comput. Vis. Pattern Recognit., 2010, pp. 2241-2248.
28. H. Niknejad, S. Mita, D. McAllester, and T. Naito, "Vision-based vehicle detection for nighttime with discriminately trained mixture of weighted deformable part models," in Proc. 14th IEEE ITSC, 2011, pp. 1560-1565.
29. M. Enzweiler, A. Eigenstetter, B. Schiele, and D. M. Gavrila, "Multi-cue pedestrian classification with partial occlusion handling," in Proc. IEEE Comput. Vis. Pattern Recognit., 2010, pp. 990-997.
30. X. Zhang, N. Zheng, Y. He, and F. Wang, "Vehicle detection using an extended hidden random field model," in Proc. 14th IEEE ITSC, Oct. 2011, pp. 1555-1559.
31. Q. Yuan, A. Thangali, V. Ablavsky, and S. Sclaroff, "Learning a family of detectors via multiplicative kernels," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 3, pp. 514-530, Mar. 2011.
32. S. Dasgupta and D. J. Hsu, "Hierarchical sampling for active learning," in Proc. Int. Conf. Mach. Learn., 2008, pp. 208-215.
33. A. J. Joshi and F. Porikli, "Scene adaptive human detection with incremental active learning," in Proc. ICPR, 2010, pp. 2760-2763.
34. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," in Proc. IEEE Comput. Vis. Pattern Recognit. Conf., 2001, pp. I-511-I-518.
35. Y. Freund and R. Schapire, "A short introduction to boosting," J. Jpn. Soc. Artif. Intell., vol. 14, no. 5, pp. 771-780, Sep. 1999.
36. D. Cohn, L. Atlas, and R. Ladner, "Improving generalization with active learning," Mach. Learn., vol. 15, no. 2, pp. 201-221, May 1994.
37. Z. Sun, G. Bebis, and R. Miller, "Monocular precrash vehicle detection: Features and classifiers," IEEE Trans. Image Process., vol. 15, no. 7, pp. 2019-2034, Jul. 2006. (Pubitemid 43985079)
38. B. Settles, "Active Learning Literature Survey," Univ. of Wisconsin-Madison, Madison, WI, USA, Comput. Sci. Tech. Rep. 1648, 2009.
39. Number of U.S. Aircraft, Vehicles, Vessels, and Other Conveyances, Bureau of Transportation Statistics-National Transportation Statistics, Washington. DC, USA, 2012.
40. C. Cortes and V. Vapnik, "Support vector networks," Mach. Learn., vol. 20, no. 3, pp. 273-297, Sep. 1995.
41. R. Gale and L. S. Shapley, "College admissions and the stability of marriage," Amer. Math. Mon., vol. 69, no. 1, pp. 9-14, Jan. 1962.
42. C.-C. Chang and C.-J. Lin, "LIBSVM: A library for support vector machines," ACM Trans. Intell. Syst. Technol., vol. 2, no. 3, pp. 27:1-27:27, Apr. 2011. [Online]. Available: http://www.csie.ntu.edu.tw/~cjlin/ libsvm
43. H.-T. Lin, C.-J. Lin, and R. C. Weng, "A note on Platt's probabilistic outputs for support vector machines," Mach. Learn., vol. 68, no. 3, pp. 267-276, Oct. 2007. (Pubitemid 47312490)
44. P. F. Felzenszwalb, R. B. Girshick, and D. McAllester, Discriminatively trained deformable part models, release 4. [Online]. Available: http://people.cs.uchicago.edu/pff/latent-release4/
45. P. Viola and M. Jones, "Fast and robust classification using asymmetric adaboost and a detector cascade," in Proc. Adv. Neural Inf. Process. Syst., 2002, vol. 14, pp. 1311-1318.
46. S. Sivaraman, B. T. Morris, and M. M. Trivedi, "Learning multi-lane trajectories using vehicle-based vision," in Proc. IEEE Int. Conf. Comput. Vis. Workshop, 2011, pp. 2070-2076.