东南大学学报（英文版）2017，Vol.33Issue(4)：426-431,6.DOI:10.3969/j.issn.1003-7985.2017.04.006
基于光流和特征点匹配相融合的低动态载体速度计算方法
A calculation method for low dynamic vehicle velocity based on fusion of optical flow and feature point matching
摘要
Abstract
Aiming at the problem of the low accuracy of low dynamic vehicle velocity under the environment of uneven distribution of light intensity,an improved adaptive Kalman filter method for the velocity error estimate by the fusion of optical flow tracking and scale invariant feature transform (SIFT) is proposed.The algorithm introduces a nonlinear fuzzy membership function and the filter residual for the noise covariance matrix in the adaptive adjustment process.In the process of calculating the velocity of the vehicle,the tracking and matching of the inter-frame displacement and the vehicle velocity calculation are carried out by using the optical flow tracing and the SIFT methods,respectively.Meanwhile,the velocity difference between the outputs of these two methods is used as the observation of the improved adaptive Kalman filter.Finally,the velocity calculated by the optical flow method is corrected by using the velocity error estimate of the output of the modified adaptive Kalman filter.The results of semi-physical experiments show that the maximum velocity error of the fusion algorithm is decreased by 29％ than that of the optical flow method,and the computation time is reduced by 80％ compared with the SIFT method.关键词
速度/光流法/特征点匹配/光强分布不均匀Key words
velocity/optical flow/feature point matching/non-uniform light intensity distribution分类
信息技术与安全科学引用本文复制引用
柳笛,陈熙源..基于光流和特征点匹配相融合的低动态载体速度计算方法[J].东南大学学报（英文版）,2017,33(4):426-431,6.基金项目
The National Natural Science Foundation of China (No.51375087,51405203),the Transformation Program of Science and Technology Achievements of Jiangsu Province (No.BA2016139). （No.51375087,51405203）
