Computing camera rotation from image sequences can be used for image stabilization, and when the camera rotation is known the computation of translation and scene structure are much simplified as well. A robust approach for recovering camera rotation is presented, which does not assume any specific scene structure (e.g. no planar surface is required), and which avoids prior computation of the epipole. Given two images taken from two different viewing positions, the rotation matrix between the images can be computed from any three homography matrices. The homographies are computed using the trilinear tensor which describes the relations between the projections of a 3D point into three images. The entire computation is linear for small angles, and is therefore fast and stable. Iterating the linear computation can then be used to recover larger rotations as well.
|Number of pages
|Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
|Published - 1996
|Proceedings of the 1996 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - San Francisco, CA, USA
Duration: 18 Jun 1996 → 20 Jun 1996