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Approximate N-View Stereo

  • Kiriakos N. Kutulakos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1842)

Abstract

This paper introduces a new multi-view reconstruction problem called approximate N-view stereo. The goal of this problem is to recover a one-parameter family of volumes that are increasingly tighter supersets of an unknown, arbitrarily-shaped 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 provably-correct for arbitrary discrete scenes (i.e., for unknown, arbitrarily-shaped Lambertian scenes that are defined by a finite set of voxels and are viewed from N arbitrarily-distributed 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.

Keywords

Calibration Error Discrete Image Scene Point View Stereo Approximate Shape 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Kiriakos N. Kutulakos
    • 1
  1. 1.Department of Computer Science & Department of DermatologyUniversity of RochesterRochesterUSA

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