Carved Visual Hulls for Image-Based Modeling

  • Yasutaka Furukawa
  • Jean Ponce
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3951)


This article presents a novel method for acquiring high-quality solid models of complex 3D shapes from multiple calibrated photographs. After the purely geometric constraints associated with the silhouettes found in each image have been used to construct a coarse surface approximation in the form of a visual hull, photoconsistency constraints are enforced in three consecutive steps: (1) the rims where the surface grazes the visual hull are first identified through dynamic programming; (2) with the rims now fixed, the visual hull is carved using graph cuts to globally optimize the photoconsistency of the surface and recover its main features; (3) an iterative (local) refinement step is finally used to recover fine surface details. The proposed approach has been implemented, and experiments with six real data sets are presented, along with qualitative comparisons with several state-of-the-art image-based-modeling algorithms.


Image Discrepancy Surface Detail Visual Hull Frontier Point Apparent Contour 
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 2006

Authors and Affiliations

  • Yasutaka Furukawa
    • 1
  • Jean Ponce
    • 1
    • 2
  1. 1.Department of Computer ScienceUniversity of Illinois at Urbana ChampaignUSA
  2. 2.Département d’Informatique, Ecole Normale SupérieureParisFrance

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