We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
We present a new approach to appearance-based object recognition, which captures the relationships between multiple model views and exploits them to improve recognition performanc...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
Stochastic tracking of structured models in monolithic state spaces often requires modeling complex distributions that are difficult to represent with either parametric or sample...
Leonid Taycher, John W. Fisher III, Trevor Darrell
This paper isconcerned with learning the canonical gray scalestructure of the images of a classof objects. Structure is defined in terms of the geometry and layout of salientimage...
Image texture can arise not only from surface albedo variations (2D texture) but also from surface height variations (3D texture). Since the appearance of 3D texture depends on th...