Vision-based attitude estimation for indoor navigation using Vanishing Points and lines

A novel method for vision-based indoor attitude aiding is described in this paper. A strapdown Inertial Navigation Systems (INS) with low-cost Micro-Electrical Micro-Mechanical (MEMS) sensors is augmented by a mono-camera. Line features are detected and analyzed using the concept of Vanishing Points (VPs) and Vanishing Lines (VLs). By exploiting geometrical constraints inside buildings, long-term stable attitude information is extracted. The performance of this aiding method is analyzed in turntable experiments and demonstrated in field test within an Integrated Pedestrian Navigation System (IPNS). It is shown that the proposed method effectively eliminates attitude drift in indoor environments and is real-time capable.