Global homography calibration for monocular vision-based pose measurement of mobile robots

Abstract

Compared with the size of a calibration board, the inspected area within the camera field of view is much bigger in many applications such as visual surveillance systems. In this paper, we present a global image-to-ground homography calibration method to obtain the mapping between the image and the planar scene lying in the whole camera field of view. The calibration approach is proposed by fusing multiple local homography matrices, with each of them only reflecting the relationship between a small calibration board and its corresponding small image part. By further calibrating a height-related homography, visual measurement can be extended for arbitrary planar surfaces with known heights. The proposed method presents such merits as no requirement for camera internal parameters, high calibration accuracy, and ease of implementation. Experimental results show that (1) the proposed global homography method achieves more accurate measurement results than the local homography method; (2) the height-related homography is calibrated with high accuracy; (3) the proposed approach can be used for mobile robot localization with accuracy close to the performance limit of a monocular camera.