LVO: Line only stereo Visual Odometry

Visual odometry in sparsely textured environments is still a difficult task. Point feature based approaches are well researched, but they need enough texture to yield good results. Recently, line features moved into focus as they only need structure and no texture. Indoor scenes are typically rich in structure. This is why line features are very well suited for this task. A line represents many points and, thus, provides a higher accuracy than a single point. We present a line-only approach that runs stable in textureless environments while achieving real-time performance. Our approach can compete well with existing point- and line-based methods and outperforms existing line-only methods. We developed a tracking method for line-segments that works well without descriptors. Additionally, we propose a heuristic filter that improves the tracking and arbitrary matching results with lines. Furthermore, an optimization using the Cayley representation for 3D lines is used, reducing the line parameters from usually six to four. We demonstrate our performance on the EuRoC benchmark and on a synthetic scene which we built to test the algorithms under particularly difficult conditions.