Estimation of Camera Parameters from a Single Moving Camera using Quaternion-based Interpolation of 3D Trajectory

This paper presents a new quaternion-based method to estimate the camera parameters in a single video stream to interpolate 3D trajectory of the moving camera with camera parameters. We assume that the camera looks at three fixed points while translating and rotating in 3D space. To estimate the camera parameters, we get a set of nonlinear equations derived from a geometric perspective camera model. We have a large number of image frames to find each camera parameters while the number of unknown camera model parameters cannot be determined from a single frame. In order to solve this problem, we used interpolation to approximate camera movement in both translation and rotation. This was done using the concept of control node set at the specific frame in the video stream. The camera movement is based on acceleration level control while satisfying physical constraints. The control node is the set of variables used to determine acceleration-based interpolated equation used for data fitting. In this process, we used quaternion to interpolate orientation of the camera. The acceleration-based data fitting problem is solved using nonlinear parameter optimization solver, GRG2. Our experimental results show that this approach to estimate camera parameters and 3D trajectory of the camera moment is robust enough to handle image sequences of a common scene without sudden change in camera moment.