Effective pedestrian detection and counting at bus stops

5th Latin American Robotic Symposium, LARS 2008

Volumn , Issue , 2008, Pages 158-163

  García Bunster, Guillermo ^a   Torres Torriti, Miguel ^a  

^a PONTIFICIA UNIVERSIDAD CATÓLICA DE CHILE   (Chile)

Author keywords

Background subtraction; Density based demand estimation.; Haar features; Pedestrian counting; Pedestrian detection

Indexed keywords

BUS TERMINALS; BUS TRANSPORTATION; BUSES; ROBOTICS;

BACKGROUND SUBTRACTION; DEMAND ESTIMATION; HAAR FEATURES; PEDESTRIAN COUNTING; PEDESTRIAN DETECTION;

FLEET OPERATIONS;

EID: 67649849836     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/LARS.2008.18     Document Type: Conference Paper

References (18)

1. C. Cortés, D. Sáez, E. Sáez, A. Núñez, A. Tirachini, "Hybrid Predictive Control Strategy for a Public Transport System with Uncertain Demand," Sixth Triennial Symposium on Transportation Analysis TRISTAN 2007, Phuket Island, Thailand, 10-15 June, 2007.
2. A. Núñez, C. Cortés, D. Sáez, M. Riquelme, "Hybrid Predictive Control for Real-time Optimization of Public Transport Systems' Operations based on Evolutionary Multiobjective Optimization," 10th International Conference on Applications of Advanced Technologies in Transportation, Athens, Greece, 27-31 May, 2008.
3. A. Nuñez, D. Sáez, C. Cortés, "Hybrid Predictive Control for the Vehicle Dynamic Routing Problem based on Evolutionary Multiobjective Optimization (EMO)," 17th IFAC World Congress, Seoul, Korea, 6-11 July, 2008.
4. F. Bu, C.-Y. Chan, "Pedestrian Detection in Transit Bus Application: Sensing Technology and Safety Solutions", Proceedings of the IEEE Intelligent Vehicle Symposium, pp. 100-105, 2005.
5. C. Papageorgiou, T. Evgeniou, and T. Poggio, "A Trainable Pedestrian Detection System," In: Proceedings of Intelligent Vehicles, 1998. pp. 241-246.
6. D.M. Gavrila, "Pedestrian Detection from a Moving Vehicle," ECCV 2000. Vol II: 37-49.
7. P. Felzenszwalb, "Learning Models for Object Detection," CVPR 2001. Vol I: 2056-1062.
8. Z. Li, K. Wang, L. Li, F.-Y. Wang, "A Review on Vision-Based Pedestrian Detection for Intelligent Vehicles," Proceedings of the IEEE International Conference on Vehicular Electronics and Safety, pp. 57-62, 2006.
9. P. Viola and M. Jones, "Rapid Object Detection using a Boosted Cascade of Simple Features," CVPR 2001. Vol I: 511-518.
10. P. Viola, M. Jones, and D. Snow, "Detecting Pedestrians Using Pattern of Motion and Appearance," ICCV 2003. pp. 734-741.
11. A. Mohan, C. Papageorgiou, and T. Poggio, "Example Based Object Detection in Images by Components," IEEE Transactions on PAMI, 23(4): 394-361, 2001.
12. K. Mikolajczyk, C. Schmid, and A. Zisserman, "Human Detection Based on a Probabilistic Assembly," ECCV 2004. Vol I: 69-82.
13. B. Wu, R. Nevatia, "Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors," International Journal of Computer Vision, v. 75, n. 2, pp. 247-266, 2007.
14. A. Ford, A. Roberts, "Colour Space Conversions,", 1998. Published online: http://www.poynton.com/PDFs/coloureq.pdf.
15. B. Browning, M. Bowling and M. Veloso, "Improbability filtering for rejecting false positives," Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3038-3043, 2002.
16. M. Piccardi, "Background subtraction techniques: a review", IEEE International Conference on Systems, Man and Cybernetics, pp. 3099-3104, 2004.
17. C. Stauffer, W.E.L. Grimson, "Adaptive background mixture modelsfor real-time tracking," Proceedings of the Conference on Computer Vision and Pattern Recognition, pp. 246-252, 1999.
18. Y. Freund, R. E. Schapire, "A decision-theoretic generalization of online learning and an application to boosting," Computational Learning Theory: Eurocolt 95, Springer-Verlag, pp.s 23-37, 1995.