Unsupervised automated panorama creation for realistic surveillance scenes through weighted mutual information registration

摘要

Automated panorama creation usually requires camera calibration or extensive knowledge of camera locations and relations to each other. Registration problems are often solved by these same camera parameters or the result of complex point matching schemes. This paper presents a novel automated panorama creation algorithm by using an affine transformation search based on maximized mutual information (MMI). MMI techniques are often limited to airborne and satellite imagery or medical images, but we can show that a simple MMI algorithm very well approximates realistic scenes of varying depth distortion. This study was performed on stationary color surveillance video cameras and proves extremely worthwhile in any system with limited or no a priori camera-to-camera parameters. This algorithm is quite robust on a very large range of strict- to nearly-affine related scenes, and provides a great approximation for the overlap regions in scenes related by a projective homography. Practical considerations were surprisingly significant in molding the development of this robust and versatile algorithm.