Multi-frame estimation of planar motion

Traditional plane alignment techniques are typically performed between pair s of frames. In this paper, we present a method for extending existing two- frame planar motion estimation techniques into a simultaneous multi-frame e stimation, by exploiting multiframe subspace constraints of planar surfaces . The paper has three main contributions: 1) we show that when the camera c alibration does not change, the collection of all parametric image motions of a planar surface in the scene across multiple frames is embedded in a lo w dimensional linear subspace; 2) we show that the relative image motion of multiple planar surfaces across multiple frames is embedded in a yet lower dimensional linear subspace, even with varying camera calibration; and 3) we show how these multi-frame constraints can be incorporated into simultan eous multi-frame estimation of planar motion, without explicitly recovering any 3D information, or camera calibration. The resulting multi-frame estim ation process is more constrained than the individual two-frame estimations , leading to more accurate alignment, even when applied to small image regi ons.