|Title||Relative Pose Estimation from Straight Lines using Parallel Line Clustering and its Application to Monocular Visual Odometry|
|Publication Type||Conference Paper|
|Year of Publication||2016|
|Authors||von Schmude, N, Lothe, P, Jähne, B|
|Conference Name||Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications|
This paper tackles the problem of relative pose estimation between two monocular camera images in textureless scenes. Due to a lack of point matches, point-based approaches such as the 5-point algorithm often fail when used in these scenarios. Therefore we investigate relative pose estimation from line observations. We propose a new approach in which the relative pose estimation from lines is extended by a 3D line direction estimation step. The estimated line directions serve to improve the robustness and the efficiency of all processing phases: they enable us to guide the matching of line features and allow an efficient calculation of the relative pose. First, we describe in detail the novel 3D line direction estimation from a single image by clustering of parallel lines in the world. Secondly, we propose an innovative guided matching in which only clusters of lines with corresponding 3D line directions are considered. Thirdly, we introduce the new relative pose estimation based on 3 D line directions. Finally, we combine all steps to a visual odometry system. We evaluate the different steps on synthetic and real sequences and demonstrate that in the targeted scenarios we outperform the state-of-the-art in both accuracy and computation time.