Dense shape reconstruction of a moving object under arbitrary, unknown lighting

Abstract

We present a method for shape reconstruction from several images of a moving object. The reconstruction is dense (up to image resolution). The method assumes that the motion is known, e.g., by tracking a small number of feature points on the object. The object is assumed Lambertian (completely matte), light sources should not be very close to the object but otherwise arbitrary, and no knowledge of lighting conditions is required. An object changes its appearance significantly when it changes its orientation relative to light sources, causing violation of the common brightness constancy assumption. While a lot of effort is devoted to deal with this violation, we demonstrate how to exploit it to recover 3D structure from 2D images. We propose a new correspondence measure that enables point matching across views of a moving object. The method has been tested both on computer simulated examples and on a real object.