A likelihood formulation for human tracking is presented based upon matching feature statistics on the surface of an articulated 3D body model. A benefit of such a formulation ove...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
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...
Hyperlinks among webpages are very important information and are widely used for webpage clustering and webpage ranking. With the explosive growth in the number of webpages availab...
Hong Zhou, Yingcai Wu, Ming-Yuen Chan, Huamin Qu, ...
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...