Indoor Manhattan spatial layout recovery from monocular videos via line matching

We present an end-to-end system for structure and motion computation in a Manhattan layout from monocular videos. Unlike most SFM algorithms that rely on point feature matching, only line matches are considered in this work. This may be convenient in indoor environment characterized by extended textureless walls, where point features may be scarce. Our system relies on the notion of “characteristic lines”, which are invariants of two views of the same parallel line pairs on a surface of known orientation. Experiments with indoor video sequences demonstrate the robustness of the proposed system.