A hypothesis testing method for multisensory data fusion

Author

Wang, Xiao-Gang ; Shen, Helen C. ; Qian, Wen-Han

Author_Institution

Dept. of Comput. Sci., Hong Kong Univ., Hong Kong

Volume

4

fYear

1998

fDate

16-20 May 1998

Firstpage

3407

Abstract

Presents a hypothesis testing method called double bound testing which is used for statistical decision-making, specifically for binary decisions. A probability decision space is defined to increase the decision flexibility. Based on the decision reached by each sensor, a combination rule is also formulated to give the global decision for the multisensor system. The proposed method offers three options for decision snaking, rather than the classical binary options. An experiment on 2D object identification was performed to demonstrate the proposed strategy

Keywords

decision theory; object recognition; probability; sensor fusion; statistical analysis; 2D object identification; binary decisions; decision flexibility; double bound testing; global decision; hypothesis testing method; multisensory data fusion; probability decision space; statistical decision-making; Bayesian methods; Computer science; Decision making; Intelligent sensors; Intelligent systems; Multisensor systems; Sensor fusion; Sensor systems; Space technology; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on

Conference_Location

Leuven

ISSN

1050-4729

Print_ISBN

0-7803-4300-X

Type

conf

DOI

10.1109/ROBOT.1998.680964

Filename

680964