In this paper, we propose a framework for QualityDriven Delivery (QDD) in distributed multimedia environments. Quality-driven delivery refers to the capacity of a system to delive...
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
Most applications manipulate structured data. Modern languages and platforms provide collection frameworks with basic data structures like lists, hashtables and trees. These data ...
Aleksandar Prokopec, Phil Bagwell, Tiark Rompf, Ma...
Many problems in computer vision can be modeled using
conditional Markov random fields (CRF). Since finding
the maximum a posteriori (MAP) solution in such models
is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...