We propose a novel framework for constrained spectral
clustering with pairwise constraints which specify whether
two objects belong to the same cluster or not. Unlike previous
m...
Zhenguo Li (The Chinese University of Hong Kong), ...
The aim of this work is to learn a shape prior model
for an object class and to improve shape matching with the
learned shape prior. Given images of example instances,
we can le...
We describe a novel device that can be used as a 2.5D
“scanner” for acquiring surface texture and shape. The device
consists of a slab of clear elastomer covered with a
refl...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
Efficient and accurate fitting of Active Appearance
Models (AAM) is a key requirement for many applications.
The most efficient fitting algorithm today is Inverse Compositional
...
Brian Amberg (University of Basel), Andrew Blake (...