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Silhouette and stereo fusion for 3D object modeling

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2 Author(s)
Esteban, C.H. ; Signal & Image Process. Dept., Ecole Nat. Superieure des Telecommun., France ; Schmitt, F.

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 multistereo correlation voting approach and a gradient vector flow diffusion. Due to the high resolution of the voting approach, a multigrid 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.

Published in:

3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings. Fourth International Conference on

Date of Conference:

6-10 Oct. 2003

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