This paper investigates the potential information provided to the user by the uncertainty measures applied to the possibility distributions associated with the spatial units of an ...
In this paper, we propose a novel dynamic discrete framework to address image morphing with application to optical flow estimation. We reformulate the problem using a number of di...
Ben Glocker, Nikos Paragios, Nikos Komodakis, Geor...
Persons may perform an activity in many different styles, or noise may cause an identical activity to have different temporal structures. We present a robust methodology for recog...
Increasing teamwork between agents typically increases the performance of a multi-agent system, at the cost of increased communication and higher computational complexity. This wo...
Matthew E. Taylor, Manish Jain, Yanquin Jin, Makot...
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...