Single Image Camera Calibration with Lenticular Arrays for Augmented Reality
We consider the problem of camera pose estimation for a scenario where the camera may have continuous and unknown changes in its focal length. Understanding frame by frame changes in camera focal length is vital to accurately estimating camera pose and vital to accurately rendering virtual objects in a scene with the correct perspective. However, most approaches to camera calibration require geometric constraints from many frames or the observation of a 3D calibration object both of which may not be feasible in augmented reality settings. This paper introduces a calibration object based on a flat lenticular array that creates a color coded light field whose observed color changes depending on the angle from which it is viewed. We derive an approach to estimate the focal length of the camera and the relative pose of an object from a single image. We characterize the performance of camera calibration across various focal lengths and camera models, and we demonstrate the advantages of the focal length estimation in rendering a virtual object in a video with constant zooming.
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)