Surface Curvature Estimation

by Peter Muir s0450876@sms.ed.ac.uk

Motivation

Curvature can be used in computer vision for e.g. object recognition or motion and pose estimation. Methods have been developed to estimate curvature in 2D images but few have been devloped for arbitrary 3D surfaces.

Overview

In Geometry an overview of the geometry involved is presented, in Curvature Estimation Techniques three methods for choosing the curvature extrema (corners) are considered as examples of the application of these ideas, and finally a list of references are presented.

Geometry Background

Given a point on a 3D surface there are two principal descriptions of the local curvature, the curvature class (the possible types are given in Table 1) and the curvature magnitude. The curvature class and the curvature magnitude can be computed from the two principal curvatures κ1 (the maximum local curvature) and κ2(the minimum local curvature).

The curvature of a surface at a given point is a measure of the deviation from the tangent (see Equation 1); the normal curvature is the curvature in the plane of the normal.

Figure 1(a) shows a cylinder intersected by a normal plane (N) in n (the normal vector to the point P) and u (the tangetial vector to the point P). u must be orthoganol to n but can can take on any direction in that plane (0° to 360°). The normal curvature is plotted in Figure 1(b) and from this κ1 and κ2 can be computed. In this example the minimum curvature (C2) is a straight line with κ = 0 and the maxminum curvature (C2) κ = 1 * radius of the circle (see Figure 1(c)).

In Figure 2 the two normals n1 (=n) and n2 (=u) are seperated by a distance L on the surface of the object. The curvature κcan be computed from n1, n2 and L. L must be computed; this is different for different geometries (e.g. Figure 3 (a) shows a cylinder, Figure 3 (b) an Elipsoid).

 

 

The mean curvature H (see Equation 3) and the Gaussian curvature K (see Equation 2) can be calculated from κ1 (p1) and κ2 (p2).

Curvature Estimation Techniques

The geometrical ideas discussed above can be used in a variety of ways. Three examples are outlined here.

Surface Triangulation Method

The surface is modelled as a series of adjacent triangles. Each triangle is flat so the curvature is concentrated at the common vertex of the triangles. Equation 4 defines the curvature when using this method.

Cross Patch Method

A cross shaped pair of points that are in two orthogonal planes are sampled and assumed to be of polynomial form. The coefficents of the polynomial can be used to estimate the surface curvature.

Partial Derivative Method

A series of smoothing filters are applied to the image; the surface curvature can be computed from first and second order partial derivatives of the smoothed image.

Further Information

  1. Surface Curvature in R.B. Fisher; From Surfaces to Objects: Computer Vision and Three Dimensional Scene Analysis , John Wiley and Sons Ltd, 1989
  2. Davis, M.H. Khotanzad, A. Flamig, D.P. Harms, S.E.; "Curvature measurement of 3D objects: evaluation and comparison of three methods" in "Image Processing, 1995. Proceedings., International Conference on"; 1995
  3. Eric W. Weisstein. "Curvature." From MathWorld--A Wolfram Web Resource
  4. Eric W. Weisstein. "Principal Curvatures." From MathWorld--A Wolfram Web Resource

Images are referenced in mouse-overs from the Further Information section.