Abstract
This evaluation for person and vehicle tracking in surveillance presented some new challenges. The dataset was large and very high-quality, but with difficult scene properties involving illumination changes, unusual lighting conditions, and complicated occlusion of objects.
Since this is a well-researched scenario [1], our submission was based primarily on our existing projects for automated object detection and tracking in surveillance. We also added several new features that are practical improvements for handling the difficulties of this dataset.
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References
Yilmaz, A., Javed, O., Shah, M.: Object tracking: A survey. ACM Comput. Surv. (2006)
Javed, O., Shah, M.: Tracking and object classification for automated surveillance. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 343–357. Springer, Heidelberg (2002)
Javed, O., Shafique, K., Shah, M.: A hierarchical approach to robust background subtraction using color and gradient information. In: IEEE Workshop on Motion and Video Computing, Orlando (2002)
Sheikh, Y., Shah, M.: Bayesian modeling of dynamic scenes for object detection. PAMI (2005)
Shafique, K., Shah, M.: A noniterative greedy algorithm for multiframe point correspondence. IEEE Trans. Pattern Anal. Mach. Intell. (2005)
White, B., Shah, M.: Automatically tuning background subtraction parameters using particle swarm optimization. In: IEEE International Conference on Multimedia and Expo., Beijing, China (2007)
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Miller, A., Basharat, A., White, B., Liu, J., Shah, M. (2008). Person and Vehicle Tracking in Surveillance Video. In: Stiefelhagen, R., Bowers, R., Fiscus, J. (eds) Multimodal Technologies for Perception of Humans. RT CLEAR 2007 2007. Lecture Notes in Computer Science, vol 4625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68585-2_14
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DOI: https://doi.org/10.1007/978-3-540-68585-2_14
Publisher Name: Springer, Berlin, Heidelberg
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