A Maximal Fuzzy Entropy Based Gaussian Clustering Algorithm for Tracking Dim Moving Point Targets in Image Sequences

After targetspsila original states were estimated by multi-frame detection method, the tracking windows in which each target may be occur were used to lower the computational load. Then all the observational data could be positioned in a observational matrix, and we used a maximal-entropy Gaussian f...

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Veröffentlicht in:	2008 International Conference on Computer Science and Software Engineering : 12-14 December 2008 Jg. 6; S. 54 - 57
Hauptverfasser:	Xingke Lian, Hamdulla, A.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2008
Schlagworte:	Clustering algorithms Clustering methods difference factor Entropy Filters Image sequences maximal-entropy gauss fuzzy clustering measurement matrix Measurement uncertainty multi-window fusion Non-effective measurement Personal digital assistants Position measurement State estimation Target tracking
ISBN:	0769533361, 9780769533360
Online-Zugang:	Volltext
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