A Fast and Simple Method for Absolute Orientation Estimation Using a Single Vanishing Point

Abstract

Absolute orientation estimation is one of the key steps in computer vision, and n 2D–3D point correspondences can be used to obtain the absolute orientation, which is known as the perspective-n-point problem (PnP). The lowest number of point correspondences is three if there is no other information, and the corresponding algorithm is called the P3P solver. In practice, the real scene may consist of some geometric information, e.g., the vanishing point. When scenes contain parallel lines, they intersect at vanishing points. Hence, to reduce the number of point correspondences and increase the computational speed, we proposed a fast and simple method for absolute orientation estimation using a single vanishing point. First, the inertial measurement unit (IMU) was used to obtain the rotation of the camera around the Y-axis (i.e., roll angle), which could simplify the orientation estimation. Then, one vanishing point was used to estimate the coarse orientation because it contained direction information in both the camera frame and world frame. Finally, our proposed method used a non-linear optimization algorithm for solution refining. The experimental results show that compared with several state-of-the-art orientation estimation solvers, our proposed method had a better performance regarding numerical stability, noise sensitivity, and computational speed in synthetic data and real images.

Keywords

• orientation estimation
• vanishing point
• perspective-n-point problem
• solution refining
• inertial measurement unit