Detection and tracking of multiple pedestrians in automotive applications

IEEE Intelligent Vehicles Symposium, Proceedings

Volumn , Issue , 2007, Pages 13-18

  Arndt, Richard ^a   Schweiger, Roland ^c   Ritter, Werner ^b   Paulus, Dietrich ^a   Löhlein, Otto ^b  

^a Institute for Computational Visualistics ^*  (Germany)

^b DAIMLER AG   (Germany)

^c UNIVERSITY OF ULM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DISTRIBUTED COMPUTER SYSTEMS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MONTE CARLO METHODS;

AUTOMOTIVE APPLICATIONS; CASCADE CLASSIFIERS; DETECTION AND TRACKING; DETECTION CRITERIA; FALSE POSITIVE; MULTIPLE PARTICLE FILTERS; PARTICLE FILTER; TRACK BEFORE DETECT;

PEDESTRIAN SAFETY;

EID: 47849096910     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ivs.2007.4290084     Document Type: Conference Paper

References (13)

1. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp. A Tutorial on Particle Filters for On-line Non-linear/Non- Gaussian Bayesian Tracking. IEEE Transactions on Signal Processing, 50(2):174-188, 2 2002.
2. Y. Boers and J. Driessen. Particle filter based detection for tracking. In Proceedings of the American Control Conference, volume 6, pages 4393-4397, Arlington, VA, USA, 6 2001.
3. J. Giebel, D. M. Gavrila, and S. Christoph. A Bayesian Framework for Multi-cue 3D Object Tracking. In Computer Vision - ECCV 2004, 8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004. Proceedings, Part IV, volume 3024, pages 241-252. Springer, 2004.
4. C. Idler, R. Schweiger, D. Paulus, M. Mählisch, and W. Ritter. Real-time vision based multi-target-tracking with particle filters in automotive applications. In IV2006, IEEE Intelligent Vehicles Symposium, pages 188-193, Tokyo, 2006.
5. M. Isard and A. Blake. CONDENSATION - conditional density propagation for visual tracking. International Journal of Computer Vision, 29(1):5-28, 1998.
6. K. Okuma, A. Taleghani, N. Freitas, J. J. Little, and L. D. G. A Boosted Particle Filter: Multitarget Detection and Tracking. In Computer Vision - ECCV 2004, 8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004. Proceedings, Part I, volume 3021, pages 28-39. Springer, 2004.
7. C. Papageorgiou, M. Oren, and T. Poggio. A general framework for object detection. In Proceedings of the Sixth International Conference on Computer Vision (ICCV'98), pages 555-562, Bombay, India, 1 1998.
8. V. Philomin, R. Duraiswami, and L. Davis. Pedestrian tracking from a moving vehicle. In Proceedings of the IEEE Intelligent Vehicles Symposium, 2000, pages 350-355, Dearborn, MI, USA, 10 2000.
9. W. Press, B. P. Flannery, S. Teukolsky, and W. Vetterling. Numerical Recipes in C. Cambridge University Press, 1993.
10. A. Shashua, Y. Gdalyahu, and G. Hayun. Pedestrian detection for driving assistance systems: Single-frame classification and system level performance. In Proceedings of the IEEE Intelligent Vehicles Symposium (IV2004), pages 1-6, Parma, Italy, 6 2004.
11. L. D. Stone, T. L. Corwin, and C. A. Barlow. Bayesian Multiple Target Tracking. Artech House Publishers, 10 1999.
12. P. Viola and M. Jones. Rapid object detection using a boosted cascade of. In Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 511-518, Kauai, Hawaii, 12 2001. IEEE Computer Society.
13. F. Xu and K. Fujimura. Pedestrian Detection and Tracking With Night Vision. IEEE Transactions on Intelligent Transportation Systems, pages 63-71, 2005.