Image Guided Geometry Inference

Songhua Xu
Yale University

Athinodoros Georghiades
Yale University

Holly Rushmeier
Yale University

Julie Dorsey
Yale University

Leonard McMillan

Image Guided Geometry Inference image

Abstract

We introduce a new method for filling holes in geometry obtained from 3D range scanners. Our method makes use of 2D images of the areas where geometric data is missing. The 2D images guide the filling using the relationship between the images and geometry learned from the existing 3D scanned data. Our method builds on existing techniques for using scanned geometry and for estimating shape from shaded images. Rather than creating plausibly filled holes, we attempt to approximate the missing geometry. We present results for scanned data from both triangulation and time-of-flight scanners for various types of materials. To quantitatively validate our proposed method, we also compare the filled areas with ground-truth data.

Paper