Camera orientation estimation using voting approach on the Gaussian sphere for in-vehicle camera

Abstract

Calibration of a vehicle camera is a key technology for advanced driver assistance systems (ADAS). This paper presents a novel estimation method to measure the orientation of a camera that is mounted on a driving vehicle. By considering the characteristics of vehicle cameras and driving environment, we detect three orthogonal vanishing points as a basis of the imaging geometry. The proposed method consists of three steps: i) detection of lines projected to the Gaussian sphere and extraction of the plane normal, ii) estimation of the vanishing point about the optical axis using linear Hough transform, and iii) voting for the rest two vanishing points using circular histogram. The proposed method increases both accuracy and stability by considering the practical driving situation using sequentially estimated three vanishing points. In addition, we can rapidly estimate the orientation by converting the voting space into a 2D plane at each stage. As a result, the proposed method can quickly and accurately estimate the orientation of the vehicle camera in a normal driving situation. © 2019 Optical Society of America.