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.