Abstract
We present a new people tracking method for human height mounted camera, e.g. the one attached near information or advertising stand. We use state-of-the-art particle filter approach and improve it by explicitly modeling of object visibility which makes the method able to cope with difficult object overlapping. We employ our own method based on online-boosting classifiers to resolve occlusions and show that it is well suited for tracking multiple objects. In addition to training an online-classifier which is updated each frame we propose to store object appearance and update it with a certain lag. It helps to correctly handle situations when a person enters the scene while another one leaves it at the same time. We demonstrate the perfomance of our algorithm and advantages of our contributions on our own video dataset.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Andriyenko, A., Schindler, K.: Globally optimal multi-target tracking on a hexagonal lattice. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6311, pp. 466–479. Springer, Heidelberg (2010)
Berclaz, J., Fleuret, F., Fua, F.: Robust people tracking with global trajectory optimization. In: CVPR (2006)
Breitenstein, M.D., Reichlin, F., Leibe, B., Koller-Meier, E., Van Gool, L.: Robust tracking-by-detection using a detector confidence particle filter. In: ICCV (2009)
Bugeau, A., Perez, P.: Track and cut: simultaneous tracking and segmentation of multiple objects with graph cuts. ACM J. on Image and Video Processing (2008)
Ferrari, V., Marin-Jimenez, M., Zisserman, A.: Progressive search space reduction for human pose estimation. In: CVPR (2008)
Fortmann, T., Shalom, Y.B., Scheffe, M.: Sonar tracking of multiple targets using joint probabilistic data association. IEEE J. Oceanic Engineering 8(3), 173–184 (1983)
Grabner, H., Bischof, H.: On-line boosting and vision. In: CVPR (2006)
Hue, C., Le Cadre, J.P., Perez, P.: Sequential monte carlo methods for multiple target tracking and data fusion. IEEE Tr. Signal Processing 50(1), 309–325 (2002)
Isard, M., MacCormick, J.: Bramble: a bayesian multiple-blob tracker. In: ICCV (2001)
Isard, M., Blake, A.: Condensation - conditional density propagation for visual tracking. International Journal of Computer Vision 29, 5–28 (1998)
Kang, J., Cohen, I., Medioni, G.: Tracking people in crowded scenes across multiple cameras. In: ACCV (2004)
Khan, S., Shah, M.: Tracking people in presence of occlusion. In: ACCV (2000)
Kuhn, H.: The hungarian method for solving the assignment problem. Naval Research Logistics Quart. 2, 83–97 (1955)
Li, Y., Huang, C., Nevatia, R.: Learning to associate: Hybridboosted multi-target tracker for crowded scene. In: CVPR (2009)
Li, Z., Yuan, L., Nevatia, R.: Global data association for multi-object tracking using network flows. In: CVPR (2008)
Mitzel, D., Horbert, E., Ess, A., Leibe, B.: Multi-person tracking with sparse detection and continuous segmentation. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6311, pp. 397–410. Springer, Heidelberg (2010)
Okuma, K., Taleghani, A., de Freitas, N., Little, J.J., Lowe, D.G.: A boosted particle filter: Multitarget detection and tracking. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 28–39. Springer, Heidelberg (2004)
Reid, D.: An algorithm for tracking multiple targets. IEEE Trans. Automatic Control 24(6), 843–854 (1979)
Song, B., Jeng, T.-Y., Staudt, E., Roy-Chowdhury, A.K.: A stochastic graph evolution framework for robust multi-target tracking. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6311, pp. 605–619. Springer, Heidelberg (2010)
Yilmaz, A., Javed, O., Shah, M.: Object tracking: A survey. ACM J. Computing Surveys 38(4) (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kononov, V., Konushin, V., Konushin, A. (2011). People Tracking Algorithm for Human Height Mounted Cameras. In: Mester, R., Felsberg, M. (eds) Pattern Recognition. DAGM 2011. Lecture Notes in Computer Science, vol 6835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23123-0_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-23123-0_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23122-3
Online ISBN: 978-3-642-23123-0
eBook Packages: Computer ScienceComputer Science (R0)