Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
Abstract—Models that can efficiently, compactly, and semantically represent potential users are important tools for human-robot interaction applications. We model a person as a p...
Learning good image priors is of utmost importance for the study of vision, computer vision and image processing applications. Learning priors and optimizing over whole images can...
We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition appro...
Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Andrew...
Augmenting cloth in real video is a challenging task because cloth performs complex motions and deformations and produces complex shading on the surface. Therefore, for a realisti...