In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function's smoothnes...
In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
We are interested in modeling the variability of different images of the same scene, or class of objects, obtained by changing the imaging conditions, for instance the viewpoint o...
Jeremy D. Jackson, Anthony J. Yezzi, Stefano Soatt...
Abstract— We present a novel combination of motion planning techniques to compute motion plans for robotic arms. We compute plans that move the arm as close as possible to the go...
Ioan Alexandru Sucan, Mrinal Kalakrishnan, Sachin ...
In this paper we propose a novel method for generic object localization. The method is based on modeling the object as a graph at two levels: a local substructural representation ...