Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
In many visual tracking and surveillance systems, it is important to initialize a background model using a training video sequence which may include foreground objects. In such a c...
We develop a method for learning the spatial statistics of optical flow fields from a novel training database. Training flow fields are constructed using range images of natur...
Visualization users are increasingly in need of techniques for assessing quantitative uncertainty and error in the images produced. Statistical segmentation algorithms compute the...
Joe Michael Kniss, Robert L. Van Uitert Jr., Abrah...
We revisit the following question: what are the minimal assumptions needed to construct statistically-hiding commitment schemes? Naor et al. show how to construct such schemes bas...
Iftach Haitner, Omer Horvitz, Jonathan Katz, Chiu-...