Computing camera rotation from image sequences can serve many computer vision applications. One direct application is image stabilization, and when the camera rotation is known the computation of camera translation and 3D scene structure are much simpli ed. A new approach for recovering camera rotation is presented in this paper, which proves to be much more robust than existing methods by avoiding the computation of the epipole. Another bene t ofthe new approach is that it does not assume any speci c scene structure. The rotation matrix of the camera is computed explicitly from three homography matrices, recovered 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.