K Nearest Neighbor Joint Possibility Data Association Algorithm

For the problem of tracking multiple targets, the Joint Probabilistic Data Association approach has shown to be very effective in handling clutter and missed detections. However, it tends to coalesce neighboring tracks and ignores the coupling between those tracks. To avoid track coalescence, a K Ne...

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Veröffentlicht in:	2010 2nd International Conference on Information Engineering and Computer Science S. 1 - 4
Hauptverfasser:	Chen Song-lin, Xu Yi-bing, Zhu Ming
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2010
Schlagworte:	Clutter Covariance matrix Joints Measurement uncertainty Probabilistic logic Target tracking Time measurement
ISBN:	1424479398, 9781424479399
ISSN:	2156-7379
Online-Zugang:	Volltext
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