Lucas-Kanade image registration using camera parameters

The Lucas-Kanade algorithm and its variants have been successfully used for numerous works in computer vision, which include image registration as a component in the process. In this paper, we propose a Lucas-Kanade based image registration method using camera parameters. We decompose a homography into camera intrinsic and extrinsic parameters, and assume that the intrinsic parameters are given, e.g., from the EXIF information of a photograph. We then estimate only the extrinsic parameters for image registration, considering two types of camera motions, 3D rotations and full 3D motions with translations and rotations. As the known information about the camera is fully utilized, the proposed method can perform image registration more reliably. In addition, as the number of extrinsic parameters is smaller than the number of homography elements, our method runs faster than the Lucas-Kanade based registration method that estimates a homography itself.