Abstract
This work presents two main contributions to achieve robust multiple-target tracking in uncontrolled scenarios. A novel system which consists on a hierarchical architecture is proposed. Each level is devoted to one of the main tracking functionalities: target detection, low-level tracking, and high-level tasks such as target-appearance representation, or event management. Secondly, tracking performances are enhanced by on-line building and updating multiple appearance models. Successful experimental results are accomplished on sequences with significant illumination changes, grouping, splitting and occlusion events.
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References
Arulampalam, S., Maskell, S., Gordon, N., Clapp, T.: A Tutorial on PFs for On-line Non-linear/Non-Gaussian Bayesian Tracking. SP 50(2), 174–188 (2002)
Bar-Shalom, Y., Fortran, T.: Tracking and Data Association. A. Press (1988)
Collins, R., Liu, Y., Leordeanu, M.: Online Selection of Discriminative Tracking Features. PAMI 27(10), 1631–1643 (2005)
Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based Object Tracking. PAMI 25(5), 564–577 (2003)
Deutscher, J., Reid, I.: Articulated Body Motion Capture by Stochastic Search. IJCV 61(2), 185–205 (2005)
Gonzàlez, J.: Human Sequence Evaluation: The Key-frame Approach. PhD thesis, UAB, Spain (2004)
Horprasert, T., Harwood, D., Davis, L.: A Robust Background Subtraction and Shadow Detection. In: 4th ACCV, Taipei, Taiwan, vol. 1, pp. 983–988 (2000)
Isard, M., MacCormick, J.: BraMBLe: A Bayesian Multiple-Blob Tracker. In: 8th ICCV, Vancouver, Canada, vol. 2, pp. 34–41. IEEE, Los Alamitos (2001)
MacCormick, J., Blake, A.: A Probabilistic Exclusion Principle for Tracking Multiple Objects. IJCV 39(1), 57–71 (2000)
Nummiaro, K., Koller-Meier, E., Van Gool, L.: An Adaptive Color-Based Particle Filter. IVC 21(1), 99–110 (2003)
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© 2006 Springer-Verlag Berlin Heidelberg
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Rowe, D., Reid, I., Gonzàlez, J., Villanueva, J.J. (2006). Unconstrained Multiple-People Tracking. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_51
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DOI: https://doi.org/10.1007/11861898_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44412-1
Online ISBN: 978-3-540-44414-5
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