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A Quasi-Minimal Model for Paper-Like Surfaces
Perriollat, M.; Bartoli, A.;
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
17-22 June 2007
Page(s):1
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7
Abstract:
Smoothly bent paper-like surfaces are developable. They are however difficult to minimally parameterize since the number of meaningful parameters is intrinsically dependent on the actual deformation. Previous generative models are either incomplete, i.e. limited to subsets of developable surfaces, or depend on huge parameter sets. We propose a generative model governed by a quasi-minimal set of intuitive parameters, namely rules and angles. More precisely, a flat mesh is bent along guiding rules, while a number of extra rules controls the level of smoothness. The generated surface is guaranteed to be developable. A fully automatic multi-camera three dimensional reconstruction algorithm, including model-based bundle-adjustment, demonstrates our model on real images.
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