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 ...
A large photo collection downloaded from the internet spans a wide range of scenes, cameras, and photographers. In this paper we introduce several novel priors for statistics of su...
Sujit Kuthirummal, Aseem Agarwala, Dan B. Goldman,...
We present a dynamic near-regular texture (NRT) tracking algorithm nested in a lattice-based Markov-Random-Field (MRF) model of a 3D spatiotemporal space. One basic observation use...
The design and analysis of today’s complex real-time systems requires advanced methods. Due to ever growing functionality, hardware complexity and component interaction, applyin...
Tone mapping and visual adaptation are crucial for the generation of static, photorealistic images. A largely unexplored problem is the simulation of adaptation and its changes ove...