Abstract: We proposed a monocular visual location algorithm which is faster,higher precise,and more robustness than current state-of-the-art methods in a wide range,repeated,high-frequency texture features (for example,cement,lawn) scenes.We extracted ORB (oriented fast and rotated brief) feature of sequences,matched point matches of images by using KNN,then computed the fundamental matrix F and the essential matrix E and used them to compute the initial camera pose.Then we computed the rotation matrix R and the translation vector t for every pair of images,and computed the camera motion between the current and the previous image,triangulating 3-D points (structure) from 2-D image correspondences,tracking the trajectory of camera.In order to improve our algorithm,we refined the pose and structure through minimizing the reprojection error.A test was made on our datasets which has been implemented in OpenCV/C++.The results is much better than tradition algorithm.Since it is a monocular implementation,we cannot do absolute scale estimation.

Key words: Visual location,Motion estimate,ORB,Feature matching,Feature tracking