RIFNOM: 3D Rotation-Invariant Features on Normal Maps

Abstract

This paper presents 3D rotation-invariant features on normal maps: RIFNOM.We assign a local coordinate system (CS) to each pixel by using neighbor normals to extract the 3D rotation-invariant features. These features can be used to perform interest point matching between normal maps. We can estimate 3D rotations between corresponding interest points by comparing local CSs. Experiments with normal maps of a rigid object showed the performance of the proposed method in estimating 3D rotations. We also applied the proposed method to a non-rigid object. By estimating 3D rotations between corresponding interest points, we successfully detected deformation of the object.