DocumentCode :
3466449
Title :
A review of high-level multisensor fusion: approaches and applications
Author :
Luo, Ren C. ; Su, Kuo L.
Author_Institution :
Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chia-Yi, Taiwan
fYear :
1999
fDate :
1999
Firstpage :
25
Lastpage :
31
Abstract :
The potential advantages in multisensor fusion can be obtained more accurately, concerning feature that are impossible to perceive with individual sensors, as well as in less time, and at a lower cost. The characterization most commonly encountered in the rapidly growing multisensor fusion literature based on levels of detail in the information is that of the now well known triple low level (data level), medium level (feature level) and high level (decision level). The development of high-level multisensor fusion representations is very important, in the construction of advanced intelligent systems. The paper begins with a review on the fundamental principles about high-level multisensor fusion, together with some of the applications. Finally, we compare the decision algorithms in the high-level multisensor fusion
Keywords :
artificial intelligence; decision theory; information theory; probability; sensor fusion; statistical analysis; data level; decision level; decision theory; feature level; high-level representations; information theory; intelligent systems; multisensor fusion; probability; statistical analysis; Automation; Bayesian methods; Humans; Inference algorithms; Intelligent sensors; Intelligent systems; Laboratories; Sensor fusion; Sensor phenomena and characterization; Sensor systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1999. MFI '99. Proceedings. 1999 IEEE/SICE/RSJ International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7803-5801-5
Type :
conf
DOI :
10.1109/MFI.1999.815960
Filename :
815960
Link To Document :
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