We propose a novel approach to designing algorithms for
object tracking based on fusing multiple observation models.
As the space of possible observation models is too large
for...
We propose a novel approach to unsupervised facial image
alignment. Differently from previous approaches, that
are confined to affine transformations on either the entire
face o...
Scenes with cast shadows can produce complex sets of
images. These images cannot be well approximated by lowdimensional
linear subspaces. However, in this paper we
show that the...
We present an image restoration method that leverages
a large database of images gathered from the web. Given
an input image, we execute an efficient visual search to
find the c...
Kevin Dale, Micah K. Johnson, Kalyan Sunkavalli, W...
We cast some new insights into solving the digital matting
problem by treating it as a semi-supervised learning
task in machine learning. A local learning based approach
and a g...