Geometry-aware Video Registration

Abstract

We present a new method for the accurate registration of video sequences of a real object over its dense triangular mesh. The goal is to obtain an accurate video-to-geometry registration to allow the bidirectional data transfer between the 3D model and the video using the perspective projection defined by the camera model. Our solution uses two different approaches: feature-based registration by KLT video tracking, and statistic-based registration by maximizing the Mutual Information (MI) between the gradient of the frame and the gradient of the rendering of the 3D model with some illumination related properties, such as surface normals and ambient occlusion. While the first approach allows a fast registration of short sequences with simple camera movements, the MI is used to correct the drift problem that KLT tracker produces over long sequences, due to the incremental tracking and the camera motion. We demonstrate, using synthetic sequences, that the alignment error obtained with our method is smaller than the one introduced by KLT, and we show the results of some interesting and challenging real sequences of objects of different sizes, acquired under different conditions.