ON 3-DIMENSIONAL SURFACE RECONSTRUCTION METHODS
Three-dimensional surface reconstruction is an important intermediate goal of many vision systems. In this paper, we survey some of the surface reconstruction methods that can be found in the literature; we will focus on a small, recent, and important subset of the published reconstruction techniques. The techniques are classified based on the surface representation used, implicit versus explicit functions. We study some important aspects of the surface reconstruction techniques. A first aspect is viewpoint invariance of the methods. This is an important property if object recognition is the ultimate objective. We give some indication of the robustness of the various methods. Also, we determine whether the parameter estimates are biased and touch upon the sensitivity to obscuration. The latter two aspects are in particular important for fitting functions in the implicit form. We describe, in detail, a parametric reconstruction method for three-dimensional object surfaces that involves numeric grid generation techniques and variational principle formulations. This technique is invariant to rigid motion in three-space.
surface reconstruction explicit functions viewpoint invariance variational principles implicit functions least squares minimization parametric surfaces range data shape primitives