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Published Articles >> Table of Contents >> Abstract
Fourth International Conference on 3-D Digital Imaging and Modeling (3DIM '03)
p. 46
Silhouette and Stereo Fusion for 3D Object Modeling
Carlos Hernández Esteban, Ecole Nationale Supérieure des Télécommunications, France
Francis Schmitt, Ecole Nationale Supérieure des Télécommunications, France
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IM.2003.1240231
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| Abstract |
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In this paper we present a new approach to high quality 3D
object reconstruction. Starting from a calibrated sequence
of color images, the algorithm is able to reconstruct both
the 3D geometry and the texture. The core of the method is
based on a deformable model, which defines the framework
where texture and silhouette information can be fused. This
is achieved by defining two external forces based on the images:
a texture driven force and a silhouette driven force.
The texture force is computed in two steps: a multi-stereo
correlation voting approach and a gradient vector flow diffusion.
Due to the high resolution of the voting approach,
a multi-grid version of the gradient vector flow has been
developed. Concerning the silhouette force, a new formulation
of the silhouette constraint is derived. It provides a
robust way to integrate the silhouettes in the evolution algorithm.
As a consequence, we are able to recover the apparent
contours of the model at the end of the iteration process.
Finally, a texture map is computed from the original images
for the reconstructed 3D model.
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 Additional Information
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Citation:
Carlos Hernández Esteban, Francis Schmitt,
"Silhouette and Stereo Fusion for 3D Object Modeling,"
3dim,
p. 46,
Fourth International Conference on 3-D Digital Imaging and Modeling (3DIM '03),
2003
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