Robust estimation of camera ego-motion parameters
Yu Leng · Infrared and Laser Engineering · 2010
Ego-motion estimation,which can retrieve motion information of a camera by analyzing images taken by the camera at different positions,has played an important role in vision navigation.Mathematically,perfect theoretical foundation of ego-motion estimation has been developed.However,noise is always found in images,which could depress the performance of ego-motion algorithms severely.So,at present the main problem of ego-motion estimation is how to develop robust algorithms against noise in images.This paper focused on the problems of robustness of ego-motion estimation algorithms,and the main idea was to improve robustness by adopting multiple methods for ego-motion estimation and find the optimal result in them.Firstly,SIFT was used to find correspondence point pairs between two images,and a scheme to refine the correspondence point pairs was proposed.Multiple methods were adopted to estimate the fundamental matrix and the optimal estimation was found by a rule deduced from imaging process.Finally,the algorithm was testified on both simulated data and real images,and the experimental results show the feasibility for improving robustness against noise.