Abstract. This article describes an algorithm for pose or motion estimation based on clustering of parameters in the six-dimensional pose space. The parameter samples are computed ...
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 ...
Unstructured peer-to-peer lookup systems incur small constant overhead per single join or leave operation, and can easily support keyword searches. Hence, they are suitable for dy...
Boolean satisfiability (SAT) is the canonical NP-complete problem that plays an important role in AI and has many practical applications in Computer Science in general. Boolean n...
The problem of computing a maximum a posteriori (MAP) configuration is a central computational challenge associated with Markov random fields. There has been some focus on “tr...
Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwr...