A Single Directrix Quasi-Minimal Model for Paper-Like Surfaces

Mathieu Perriollat (1) , Adrien Bartoli (1)

1 LASMEA - Laboratoire des sciences et matériaux pour l'électronique et d'automatique

We are interested in reconstructing paper-like objects from images. These objects are modeled by developable surfaces and are mathematically wellunderstood. They are difcult to minimally parameterize since the number of meaningful parameters is intrinsically dependent on the actual surface. We propose a quasi-minimal model which self-adapts its set of parameters to the actual surface. More precisly, a varying number of rules is used jointly with smoothness constraints to bend a at mesh, generating the sought-after surface. We propose an algorithm for tting this model to multiple images by minimizing the point-based reprojection error. Experimental results are reported, showing that our model ts real images accurately.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Mathieu Perriollat, Adrien Bartoli. A Single Directrix Quasi-Minimal Model for Paper-Like Surfaces. Danish Machine Vision Conference, 2006, Denmark. ⟨hal-00094754⟩