Line-based SLAM considering directional distribution of line features in an urban environment

In this paper, we propose a line-based SLAM (Simultaneous Localization and Mapping) from an image sequence captured by a vehicle in consideration with the directional distribution of line features that detected in an urban environments. The proposed SLAM is based on line segments detected from objects in an urban environment, for example, road markings and buildings, that are too conspicuous to be detected. We use additional constraints regarding the line segments so that we can improve the accuracy of the SLAM. We assume that the angle of the vector of the line segments to the vehicle's direction of travel conform to four-component Gaussian mixture distribution. We define a new cost function considering the distribution and optimize the relative camera pose, position, and the 3D line segments by bundle adjustment. In addition, we make digital maps from the detected line segments. Our method increases the accuracy of localization and revises tilted lines in the digital maps. We implement our method to both the single-camera system and the multi-camera system. The accuracy of SLAM, which uses a single-camera system with our constraint, works just as well as a method that uses a multi-camera system without our constraint.