The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
The process of finding representative shape patterns from sparse datasets is a challenging task: especially for non-rigid objects, shape deformations through time can produce very...
Stefano Maludrottu, Hany Sallam, Carlo S. Regazzon...
We propose a new way of embedding shape distributions in a topological deformable template. These distributions rely on global shape descriptors corresponding to the 3D moment inva...
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
An object seen from different viewpoints results in differently deformed images. Affine-invariant shape classification must classify correctly the object, disregarding its viewpoi...