A low-cost pedestrian-detection system with a single optical camera

IEEE Transactions on Intelligent Transportation Systems

Volumn 9, Issue 1, 2008, Pages 58-67

  Cao, Xian Bin ^b,c   Qiao, Hong ^a,d,e   Keane, John ^e  

^a IEEE

^b UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^c Anhui Province Key Laboratory of Software in Computing and Communication   (China)

^d INSTITUTE OF AUTOMATION   (China)

^e UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Cascade classifier; Decomposed support vector machines (SVMs); Pedestrian detection system (PDS); Revolutionary algorithm; Small scale weighted template tree; Statistical learning

Indexed keywords

CAMERAS; INFRARED DEVICES; MOTION ESTIMATION; OPTICAL SYSTEMS; STATISTICAL METHODS; SUPPORT VECTOR MACHINES; TREES (MATHEMATICS);

CASCADE CLASSIFIERS; PEDESTRIAN-DETECTION SYSTEM (PDS); REVOLUTIONARY ALGORITHMS; SMALL-SCALE WEIGHTED TEMPLATE TREE; STATISTICAL LEARNING;

PEDESTRIAN SAFETY;

EID: 40349102103     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2007.909239     Document Type: Conference Paper

References (30)

1. F. Xu, X. Liu, and K. Fujimura, "Pedestrian detection and tracking with night vision," IEEE Trans. Intell. Tramp. Syst., vol. 6, no. 1, pp. 63-71, Mar. 2005.
2. M. Bertozzi. A. Broggi, A. Fascioli, T. Graf, and M.-M. Meinecke, "Pedestrian detection for driver assistance using multiresolution infrared vision," IEEE Trans. Veh. Technol. vol. 53, no. 6, pp. 1666-1678, Nov. 2004.
3. M. Bertozzi, A. Broggi, A. Lasagni, and M. Del Rose, "Infrared stereo vision-based pedestrian detection," in Proc. IEEE Int. Conf. Intell. Veh. Symp., Jun. 2005, pp. 24-29.
4. Y. Fang, K. Yamada, Y. Ninomiya, B. K. P. Horn, and I. Masaki, "A shapeindependent method for pedestrian detection with far-infrared images," IEEE Trans. Veh. Technol., vol. 53, no. 6, pp. 1679-1697, Nov. 2004.
5. T. Tsuji, H. Hattori, M. Watanabe, and N. Nagaoka, "Development of night-vision system," IEEE Trans. Intell. Transp. Syst., vol. 3, no. 3, pp. 203-209, Sep. 2002.
6. X. Liu and K. Fujimura, "Pedestrian detection using stereo night vision," IEEE Trans. Veh. Technol. vol. 53, no. 6, pp. 1657-1665, Nov. 2004.
7. D. M. Gavrila, J. Giebel, and S. Munder, "Vision-based pedestrian detection: The PROTECTOR system," in Proc. IEEE Int. Conf. Intell. Veh. Symp., Jun. 2004, pp. 13-18.
8. D. M. Gavrila and J. Giebel, "Shape-based pedestrian detection and tracking," in Proc. IEEE Int. Conf. Intell. Veh. Symp., Jun. 2002, vol. 1, pp. 8-14.
9. M. Bertozzi, A. Broggi, R. Chapuis, F. Chausse, A. Fascioli, and A. Tibaldi, "Shape-based pedestrian detection and localisation," in Proc. IEEE Intell. Transp. Syst., Oct. 2003, vol. 1&2, pp. 328-333.
10. B. Heisele and C. Woehler, "Motion-based recognition of pedestrians," in Proc. IEEE 14th Int. Conf. Pattern Recog., Aug. 1998, vol. 2, pp. 1325-1330.
11. Y. Ricquebourg and P. Bouthemy, "Real-time tracking of moving persons by exploiting spatio-temporal image slices," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 8, pp. 797-808, Aug. 2000.
12. C. Wohler, U. Kressel, and J. K. Anlaur, "Pedestrian recognition by classification of image sequences global approaches vs. local spatio-temporal processing," in Proc. IEEE 15th Int. Conf. Pattern Recog., Sep. 2000, vol. 2, pp. 540-544.
13. C. Curio, J. Edelbrunner, T. Kalinke, C. Tzomakas. and W. von Seelen, "Walking pedestrian recognition," IEEE Trans. Intell. Transp. Syst., vol. 1, no. 3, pp. 155-163, Sep. 2000.
14. U. Franke and S. Heinrich, "Fast obstacle detection for urban traffic situations," IEEE Trans. Intell. Transp. Syst., vol. 3, no. 3, pp. 173-181, Sep. 2002.
15. H. Elzein, S. Lakshmanan, and P. Watta, "A motion and shape-based pedestrian detection algorithm," in Proc. IEEE Int. Conf. Intell. Veh. Symp., Jun. 2003, pp. 500-504.
16. Y. W. Xu, X. B. Cao, and H. Qiao, "Alow-cost pedestrian detection system with a single optical camera," in Proc. 6th World Congr. Control Autom., 2006, vol. 10, pp. 8759-8763.
17. Y. W. Xu, X. B. Cao, H. Qiao, and F. Y. Wang, "A cascaded classifier for pedestrian detection," in Proc. IEEE Intell. Veh. Symp., Jun. 13-15, 2006, pp. 336-343.
18. D. M. Gavrila, "Pedestrian detection from a moving vehicle," in Proc. Eur. Conf. Comput. Vis., 2000, pp. 37-49.
19. P. Viola, M. Jones, and D. Snow, "Detecting pedestrians using patterns of motion and appearance," Int. J. Comput. Vis., vol. 63, no. 2, pp. 153-161, Jul. 2005.
20. A. Shashua, Y. Gdalyahu, and G. Hayun, "Pedestrian detection for driving assistance systems - Single-frame classification and system level performance," in Proc. IEEE Int. Conf. Intell. Veh. Symp., Jun. 2004, pp. 1-6.
21. L. Havasi, Z. Szlávik, and T. Sziranyi, "Higher order symmetry for non-linear classification of human walk detection," Pattern Recognit. Lett., vol. 27, no. 7, pp. 822-829, May 2006.
22. L. Andrade, S. Blunsden. and B. Fisher, "Characterization of optical flow anomalies in pedestrian traffic," in Proc. IEE Int. Symp. Imag. Crime Detection Prevention, 2005, pp. 73-78.
23. H. Qiao, F. Y. Wang, and X. B. Cao, "Application of a decomposed support vector machine algorithm in pedestrian detection from a moving vehicle," in Proc. IEEE Int. Conf. Intell. Security Informatics. 2005, pp. 662-663.
24. C. J. C. Bugres, "A tutorial on support vector machines for pattern recognition," Data Min. Knowl. Discov., vol. 2, no. 2, pp. 121-167, Jun. 1998.
25. T. Joachims, "Making large-scale SVM learning practical," in Advances in Kernel Methods-Support Vector Learning, B. Schölkopf, C. J. C. Burges, and A. J. Smola, Eds. Cambridge, MA: MIT Press, 1998.
26. P. Viola and M. Jones, "Robust real-time face detection," Int. J. Comput. Vis., vol. 57, no. 2, pp. 137-154, May 2004.
27. Y. Freund and R. E. Schapire, "A decision-theoretic generalization of online learning and an application to boosting," in Proc. EuroCOLT, 1995, pp. 23-37.
28. M. H. Alsuwaiyel and D. M. Gavrila, "On the distance transform of binary images," in Proc. IEEE Int. Conf. Imag. Sci., Syst., Technol., 2000, vol. I/II, pp. 83-86.
29. X. B. Cao, H. Qiao, F. Y. Wang, and X. Z. Zhang, "Application of cooperative co-evolution in pedestrian detection systems," in Proc. IEEE Int. Conf. Intell. Security Informatics, 2005, pp. 664-665.
30. D. M. Gavrila, "The visual analysis of human movement: A survey," Comput. Vis. Image Underst., vol. 73, no. 1, pp. 82-98, Jan. 1999.