Approximate N-view stereo

Abstract

This paper introduces a new multiview reconstruction problem called approximate Nview stereo. The goal of this problem is to recover a oneparameter family of volumes that are increasingly tighter supersets of an unknown, arbitrarilyshaped 3D scene. By studying 3D shapes that reproduce the input photographs up to a special image transformation called a shuffle transformation, we prove that (1) these shapes can be organized hierarchically into nested supersets of the scene, and (2) they can be computed using a simple algorithm called Approximate Space Carving that is provablycorrect for arbitrary discrete scenes (i.e., for unknown, arbitrarilyshaped Lambertian scenes that are defined by a finite set of voxels and are viewed from N arbitrarilydistributed viewpoints inside or around them). The approach is specifically designed to attack practical reconstruction problems, including (1) recovering shape from images with inaccurate calibration information, and (2) building coarse scene models from multiple views.