A Multiple View 3D Registration Algorithm with Statistical Error Modeling

摘要

The contribution of the paper is two-fold: Firstly, a review of the point set registration literature is given, and secondly, a novel covariance weighted least squares formula- tion of the multiple view point set registration problem is pre- sented. Point data for surface registration is commonly obtained by non-contact, 3D surface sensors such as scanning laser range finders or structured light systems. Our formulation allows the specification of anisotropic and heteroscedastic (point dependent) 3D noise distributions for each measured point.