The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Extended Target Tracking Using Gaussian Processes
Open accessAbstract
In this paper, we propose using Gaussian processes to track an extended object or group of objects, that generates multiple measurements at each scan. The shape and the kinematics of the object are simultaneously estimated, and the shape is learned online via a Gaussian process. The proposed algorithm is capable of tracking different objects with different shapes within the same surveillance region. The shape of the object is expressed analytically, with well-defined confidence intervals, which can be used for gating and association. Furthermore, we use an efficient recursive implementation of the algorithm by deriving a state space model in which the Gaussian process regression problem is cast into a state estimation problem.
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Cites
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
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
Design and Analysis of Modern Tracking Systems
Blackman, S. S., & Populi, R. (1999) · Cited by 3,509
Bar-Shalom, Y., Fortmann, T. E., & Cable, P. G. (1990) · The Journal of the Acoustical Society of America · doi:10.1121/1.398863 · Cited by 3,070
Gupta, A. K., & Nagar, D. K. (2018) · Chapman & Hall/CRC eBooks · doi:10.1201/9780203749289 · Cited by 1,295
Measuring the Objectness of Image Windows
Alexe, B., Deselaers, T., & Ferrari, V. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.28 · Cited by 1,186
Bayesian approach to extended object and cluster tracking using random matrices
Koch, J. W. (2008) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2008.4655362 · Cited by 667
Tracking of Extended Objects and Group Targets Using Random Matrices
Feldmann, M., Franken, D., & Koch, W. (2011) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2010.2101064 · Cited by 481
A framework for spatiotemporal control in the tracking of visual contours
Blake, A., Curwen, R., & Zisserman, A. (1993) · International Journal of Computer Vision · doi:10.1007/bf01469225 · Cited by 380
Neural networks and machine learning
Bishop, C. (1998) · Springer eBooks · Cited by 316
Cited by
Human Memory Update Strategy: A Multi-Layer Template Update Mechanism for Remote Visual Monitoring
Liu, S., Wang, S., Liu, X., Gandomi, A. H., Daneshmand, M., Muhammad, K., & De Albuquerque, V. H. C. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3065580 · Cited by 253
Metadata
- Authors
- Wahlstrom, N., & Ozkan, E.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2015-08
- Volume
- 63
- Issue
- 16
- Pages
- 4165-4178
- ISSN
- 1053-587X (ISSN-L)
- 1941-0476
- OpenAlex
- W2058568645
- Cited by
- 295
- References
- 23
- FWCI
- 11.26
- Type
- journal article
- Language
- en
- Open access
- green
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