The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A probabilistic exclusion principle for tracking multiple objects
Abstract
Tracking multiple targets whose models are indistinguishable is a challenging problem. Simply instantiating several independent I-body trackers is not an adequate solution, because the independent trackers can coalesce onto the best-fitting target. This paper presents an observation density for tracking which solves this problem by exhibiting a probabilistic exclusion principle. Exclusion arises naturally from a systematic derivation of the observation density, without relying on heuristics. Another important contribution of the paper is the presentation of partitioned sampling, a new sampling method for multiple object tracking. Partitioned sampling avoids the high computational load associated with fully coupled trackers, while retaining the desirable properties of coupling.
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Citations
Cites
CONDENSATION—Conditional Density Propagation for Visual Tracking
Isard, M., & Blake, A. (1998) · International Journal of Computer Vision · doi:10.1023/a:1008078328650 · Cited by 4,886
Self-citation
Cited by
Robust Monte Carlo localization for mobile robots
Thrun, S., Fox, D., Burgard, W., & Dellaert, F. (2001) · Artificial Intelligence · doi:10.1016/s0004-3702(01)00069-8 · Cited by 1,809
An adaptive color-based particle filter
Nummiaro, K., Koller-Meier, E., & Van Gool, L. (2003) · Image and Vision Computing · doi:10.1016/s0262-8856(02)00129-4 · Cited by 1,157
A Boosted Particle Filter: Multitarget Detection and Tracking
Okuma, K., Taleghani, A., de Freitas, N., Little, J. J., & Lowe, D. G. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24670-1_3 · Cited by 1,019
Articulated body motion capture by annealed particle filtering
Deutscher, J., Blake, A., & Reid, I. (2002) · Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662) · doi:10.1109/cvpr.2000.854758 · Cited by 868
Self-citationMCMC-based particle filtering for tracking a variable number of interacting targets
Khan, Z., Balch, T., & Dellaert, F. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.223 · Cited by 771
Metadata
- Authors
- MacCormick, J., & Blake, A.
- Venue
- Proceedings of the Seventh IEEE International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 1999
- Pages
- 572-578 vol.1
- OpenAlex
- W2110370029
- Cited by
- 357
- References
- 1
- FWCI
- 13.87
- Type
- conference paper
- Language
- en
- Open access
- closed
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