Automatic loop closure detection using multiple cameras for 3D indoor localization

Automated 3D modeling of building interiors is useful in applications such as virtual reality and environment mapping. We have developed a human operated backpack data acquisition system equipped with a variety of sensors such as cameras, laser scanners, and orientation measurement sensors to generate 3D models of building interiors, including uneven surfaces and stairwells. An important intermediate step in any 3D modeling system, including ours, is accurate 6 degrees of freedom localization over time. In this paper, we propose two approaches to improve localization accuracy over our previously proposed methods. First, we develop an adaptive localization algorithm which takes advantage of the environment's floor planarity whenever possible. Secondly, we show that by including all the loop closures resulting from two cameras facing away from each other, it is possible to reduce localization error in scenarios where parts of the acquisition path is retraced. We experimentally characterize the performance gains due to both schemes.