Direct Visual Odometry Using Lines for a Monocular Camera

Abstract

Most of the visual odometry is based on the matching of the feature points, or the pixel matching of the direct method. However, images have another obvious feature, i.e. the line feature. If we use the point based visual odometry in low texture images, it may result in bad performance in the experiment because of few numbers of feature points. Although in some texture-less environments, it is still possible to reliably estimate the line based on geometric elements. For example, the structured edges are obvious in the indoor scenes. In this paper, we propose a monocular visual odometry method which is based on the combination of direct method and line feature. Then we use TUM-RGB and ICL-NUIM datasets to test our algorithm. Experimental results show that our method improves the robustness and accuracy of the estimation of the position and attitude of the camera.