In this study we propose an integrated approach to the problem of 3D pose estimation. The main difference to the majority of known methods is the usage of complementary image info...
"A random or stochastic process is a mathematical model for a phenomenon
that evolves in time in an unpredictable manner from the viewpoint of the
observer. The phenomenon m...
As a well known fixed-point iteration algorithm for kernel
density mode-seeking, Mean-Shift has attracted wide attention
in pattern recognition field. To date, Mean-Shift algorit...
This paper presents Bayesian edge inference (BEI), a
single-frame super-resolution method explicitly grounded in
Bayesian inference that addresses issues common to existing
meth...
Bryan S. Morse, Dan Ventura, Kevin D. Seppi, Neil ...
We propose a method to identify and localize object
classes in images. Instead of operating at the pixel level,
we advocate the use of superpixels as the basic unit of a
class s...