DocumentCode :
353945
Title :
Random sets in data fusion: formalism to new algorithms
Author :
Mori, Shozo
Author_Institution :
Inf. Extraction & Transp. Inc., Arlington, VA, USA
Volume :
1
fYear :
2000
fDate :
10-13 July 2000
Abstract :
Although a connection between multi-object tracking and random set theory was recognized during the course of the development of multi-hypothesis tracking algorithms, it was only recently that such a connection started to be discussed based on random set theory and to be related to several algorithms based on it. This paper describes a random set formalism of a general theory of multiple object tracking, and discusses recent developments in both theory and applications in an attempt to explore further applications of random set theory to data fusion.
Keywords :
random processes; sensor fusion; set theory; state estimation; tracking; algorithms; data fusion; multi-hypothesis tracking algorithms; multiple object tracking; random set theory; Chaos; Data mining; Density functional theory; History; Probability distribution; Random sequences; Set theory; State estimation; State-space methods; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
Type :
conf
DOI :
10.1109/IFIC.2000.862690
Filename :
862690
Link To Document :
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