Data Fusion Using Improved Dempster-Shafer Evidence Theory for Vehicle Detection

Authors:
Wentao Zhao;Tao Fang;Yan Jiang
Affiliations:
Shanghai Jiao Tong University;Shanghai Jiao Tong University;Shanghai University
Venue:
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
Year:
2007

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Abstract

Data fusion is an important tool for improving the performance of detecting system when various sensors are available. The Dempster-Shafer evidence theory for fusion has similar reasoning logic with human. So we apply the data fusion method which is based on Dempster-Shafer theory, in a vehicle detecting system to increase the detection accuracy. In this paper, the Dempster-Shafer evidence theory and its problem are discussed, and an improved Reliability Revaluated Dempster-Shafer Fusion (RRDSF) algorithm is proposed and applied. The experiments show promising results and encourage us to do further work.