Automatic Camera Pose Estimation Based on Textured 3D Map Information

Abstract

To construct an intelligent space which has a distributed camera network, pre-calibration of all cameras (i.e., determining the absolute poses of each camera) is an essential task that is extremely tedious. This paper deals with automatic calibration method for the distributed camera based on 3D map information of an environment. Parameterized line features that are extracted from both a distributed camera image and the map information are transformed to Hough space and utilized for matching process in particle filter-based estimation. We evaluate the proposed method in a simulation environment with a virtual camera.