Skeletonization algorithms typically decompose an object’s
silhouette into a set of symmetric parts, offering a
powerful representation for shape categorization. However,
havi...
Alex Levinshtein, Sven Dickinson, Cristian Sminchi...
We introduce a novel parametric BRDF model that can
accurately encode a wide variety of real-world isotropic
BRDFs with a small number of parameters. The key observation
we make...
Object detection in cluttered, natural scenes has a high
complexity since many local observations compete for object
hypotheses. Voting methods provide an efficient solution
to ...
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
Context is critical for minimising ambiguity in object de-
tection. In this work, a novel context modelling framework
is proposed without the need of any prior scene segmen-
tat...