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A tracker based on a CPHD filter approach for infrared applicationsFormat | Member Price | Non-Member Price |
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Paper Abstract
Since the derivation of PHD filter, a number of track management schemes have been proposed to adapt the PHD filter for
determining the tracks of multiple objects. Nevertheless, the problem remains that such approaches can fail when targets
are too close or are crossing. In this paper, we propose to improve the tracking by maintaining a set of locally-based
trackers and managing the tracks with an assignment method. Furthermore, the new algorithm is based on a Gaussian
mixture implementation of the CPHD filter, by clustering neighbouring Gaussians before the update step and updating
each cluster with the CPHD filter update. In order to be computationally efficient, the algorithm includes gating techniques
for the local trackers and constructs local cardinality distributions for the targets and clutter within the gated regions. An
improvement in multi-object estimation performance has been experienced on both synthetic and real IR data scenarios.
Paper Details
Date Published: 5 May 2011
PDF: 12 pages
Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 80500N (5 May 2011); doi: 10.1117/12.883959
Published in SPIE Proceedings Vol. 8050:
Signal Processing, Sensor Fusion, and Target Recognition XX
Ivan Kadar, Editor(s)
PDF: 12 pages
Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 80500N (5 May 2011); doi: 10.1117/12.883959
Show Author Affiliations
Y. Petetin, CNRS, Telecom Institute/Telecom SudParis (France)
D. Clark, Heriot-Watt Univ. (United Kingdom)
D. Clark, Heriot-Watt Univ. (United Kingdom)
B. Ristic, Defence Science and Technology Organisation (Australia)
D. Maltese, SAGEM Defense & Security (France)
D. Maltese, SAGEM Defense & Security (France)
Published in SPIE Proceedings Vol. 8050:
Signal Processing, Sensor Fusion, and Target Recognition XX
Ivan Kadar, Editor(s)
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