Human Detection and Tracking under Complex Activities

Brais Cancela, M. Ortega, Manuel G. Penedo

Abstract

Multiple-target tracking is a challenging question when dealing with complex activities. Situations like partial occlusions in grouping events or sudden target orientation changes introduce complexity in the detection which is difficult to solve. In particular, when dealing with human beings, often the head is the only visible part. Techniques based in upper body achieve good results in general, but fail to provide a good tracking accuracy in the kind of situations mentioned before. We present a new methodology for provide a full tracking system under complex activities. A combination of three different techniques is used to overcome the problems mentioned before. Experimental results in sport sequences show both the speed and performance of this technique.

References

  1. Cancela, B., Ortega, M., Penedo, M. G., and Fernández, A. (2011). Solving multiple-target tracking using adaptive filters. In Lecture Notes in Computer Science (ICIAR 2011), volume 6753, pages 416 - 425.
  2. Comaniciu, D., Ramesh, V., and Meer, P. (2000). Realtime tracking of non-rigid objects using mean shift. In Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on, volume 2, pages 142 -149 vol.2.
  3. Dalal, N. and Triggs, B. (2005). Histograms of oriented gradients for human detection. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 886 - 893.
  4. Desai, C., Ramanan, D., and Fowlkes, C. (2009). Discriminative models for multi-class object layout. In Computer Vision, 2009 IEEE 12th International Conference on, pages 229 -236.
  5. Kalman, R. (1960). A new approach to linear filtering and prediction problems. Transactions of the ASMEJournal of Basic Engineering, 82(Series D):35-45.
  6. Li, M., Zhang, Z., Huang, K., and Tan, T. (2008). Estimating the number of people in crowded scenes by mid based foreground segmentation and head-shoulder detection. In Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, pages 1 -4.
  7. Li, M., Zhang, Z., Huang, K., and Tan, T. (2009). Rapid and robust human detection and tracking based on omegashape features. In 16th IEEE International Conference on Image Processing (ICIP), pages 2545 - 2548.
  8. Porikli, F. (2005). Integral histogram: a fast way to extract histograms in cartesian spaces. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 829 - 836.
  9. Rodriguez, M., Sivic, J., Laptev, I., and Audibert, J.-Y. (2011). Density-aware person detection and tracking in crowds. In Proceedings of the International Conference on Computer Vision (ICCV).
  10. Stauffer, C. and Grimson, W. E. L. (1999). Adaptive background mixture models for real-time tracking. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 2, pages 246- 252.
  11. Viola, P. and Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on, volume 1, pages I-511 - I-518.
  12. Zhan, B., Monekosso, D., Remagnino, P., Velastin, S., and Xu, L.-Q. (2008). Crowd analysis: a survey. Machine Vision and Applications, 19:345-357.
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Paper Citation


in Harvard Style

Cancela B., Ortega M. and Penedo M. (2013). Human Detection and Tracking under Complex Activities . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 370-374. DOI: 10.5220/0004201503700374


in Bibtex Style

@conference{visapp13,
author={Brais Cancela and M. Ortega and Manuel G. Penedo},
title={Human Detection and Tracking under Complex Activities},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={370-374},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004201503700374},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Human Detection and Tracking under Complex Activities
SN - 978-989-8565-48-8
AU - Cancela B.
AU - Ortega M.
AU - Penedo M.
PY - 2013
SP - 370
EP - 374
DO - 10.5220/0004201503700374