Estimating planar surface orientation using bispectral analysis.

Abstract

In this correspondence, we propose a direct method for estimating the orientation of a plane from a single view under perspective projection. Assuming that the underlying planar texture has random phase, we show that the nonlinearities introduced by perspective projection lead to higher order correlations in the frequency domain. We also empirically show that these correlations are proportional to the orientation of the plane. Minimization of these correlations, using tools from polyspectral analysis, yields the orientation of the plane. We show the efficacy of this technique on synthetic and natural images.