2017 年 83 巻 12 号 p. 1209-1215
In this paper, a novel method for 6 degrees of freedom (DoF) localization of a single spherical camera in a man-made environment is proposed. Taking advantage of the various line features that are usually present in such an environment, a technique to match the 2D line feature information inside a spherical image to the 3D line segment information available in a known 3D model of the environment is developed. There are two main challenges to be overcome. First is the detection of the line feature information in a spherical image and its abstraction into a descriptor that is compatible with the 3D line feature information in the model. Second is to evaluate similarity of the line feature information from the 2D image and that from arbitrary 6 DoF poses in the 3D environment model in order to localize the camera. To deal with the former, a randomized hough transform with spherical gradient-based filtering is used to accurately detect line features in the image and create a line feature descriptor. The same descriptor is created from arbitrary 6 DoF poses in the 3D model. Then, to deal with the latter, the Earth Mover's Distance (EMD) is used to evaluate their similarity. The proposed method was evaluated in a real environment with its 3D model. The results demonstrated that it can effectively estimate the 6 DoF pose of a spherical camera using a single image.