TY - JOUR
T1 - Projective visual Hulls
AU - Lazebnik, Svetlana
AU - Furukawa, Yasutaka
AU - Ponce, Jean
N1 - Funding Information:
This research was partially supported by the UIUC Campus Research Board and by the National Science Foundation under grants IRI-990709, IIS-0308087, and IIS-0312438. The authors would like to thank Jodi Blumen-feld and Steven R. Leigh of the UIUC Anthropology Department for providing the skull, and Jean-Sébastien Franco and Edmond Boyer for making the implementation of their EPVH algorithm publicly available. We are also grateful to Edmond Boyer for providing the gourd data set and for discussions that have led to some of the work presented in this article.
PY - 2007/8
Y1 - 2007/8
N2 - This article presents a novel method for computing the visual hull of a solid bounded by a smooth surface and observed by a finite set of cameras. The visual hull is the intersection of the visual cones formed by back-projecting the silhouettes found in the corresponding images. We characterize its surface as a generalized polyhedron whose faces are visual cone patches; edges are intersection curves between two viewing cones; and vertices are frontier points where the intersection of two cones is singular, or intersection points where triples of cones meet. We use the mathematical framework of oriented projective differential geometry to develop an image-based algorithm for computing the visual hull. This algorithm works in a weakly calibrated setting - that is, it only requires projective camera matrices or, equivalently, fundamental matrices for each pair of cameras. The promise of the proposed algorithm is demonstrated with experiments on several challenging data sets and a comparison to another state-of-the-art method.
AB - This article presents a novel method for computing the visual hull of a solid bounded by a smooth surface and observed by a finite set of cameras. The visual hull is the intersection of the visual cones formed by back-projecting the silhouettes found in the corresponding images. We characterize its surface as a generalized polyhedron whose faces are visual cone patches; edges are intersection curves between two viewing cones; and vertices are frontier points where the intersection of two cones is singular, or intersection points where triples of cones meet. We use the mathematical framework of oriented projective differential geometry to develop an image-based algorithm for computing the visual hull. This algorithm works in a weakly calibrated setting - that is, it only requires projective camera matrices or, equivalently, fundamental matrices for each pair of cameras. The promise of the proposed algorithm is demonstrated with experiments on several challenging data sets and a comparison to another state-of-the-art method.
KW - 3D photography
KW - Frontier point
KW - Oriented projective geometry
KW - Projective differential geometry
KW - Projective reconstruction
KW - Silhouette
KW - Visual hull
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U2 - 10.1007/s11263-006-0008-x
DO - 10.1007/s11263-006-0008-x
M3 - Article
AN - SCOPUS:34248329556
SN - 0920-5691
VL - 74
SP - 137
EP - 165
JO - International Journal of Computer Vision
JF - International Journal of Computer Vision
IS - 2
ER -