This paper addresses the problem of efficiently solving large-scale energy minimization problems encountered in computer vision. We propose an energy-aware method for merging ran...
Taesup Kim, Sebastian Nowozin, Pushmeet Kohli, Cha...
In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based ...
Generalized Belief Propagation (gbp) has proven to be a promising technique for performing inference on Markov random fields (mrfs). However, its heavy computational cost and large...
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
In this paper, we present a purely incremental, scalable algorithm for the detection of elliptical shapes in images. Our method uses an incremental version of the Random Hough Tra...