Title :
Dempster-Shafer reasoning with application multisensor object recognition system
Author :
Zhang, Xin-Man ; Han, Jiu-qiang ; Xu, Xue-Bin
Author_Institution :
Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., China
Abstract :
Firstly by analyzing comprehensively the different sensor acquisitions based on normal distribution, a mathematical model is established to attain the basic probability assignments. Following this a multisensor data fusion method-based Dempster-Shafer reasoning is proposed to resolve object recognition problems. Offered by multilevel accumulation of assignments recursively the fusion estimates based on global information is obtained to testify the recognition performance. It is optimal than that of a single sensor with an average decline 74 percent of uncertainty value in a case study of pyrites recognition system, thereby demonstrating the effectiveness and correctness of this approach.
Keywords :
inference mechanisms; normal distribution; object recognition; sensor fusion; Dempster-Shafer reasoning; multisensor data fusion method; multisensor object recognition system; normal distribution; pyrites recognition system; sensor acquisitions; Continuing education; Electronic mail; Information analysis; Mathematical model; Object detection; Object recognition; Recursive estimation; Sensor systems; Testing; Uncertainty;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1382328
