This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), w...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
Abstract. Variational problems, which are commonly used to solve lowlevel vision tasks, are typically minimized via a local, iterative optimization strategy, e.g. gradient descent....
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...
Abstract. In this paper, we analyze a hybridizable discontinuous Galerkin method for numerically solving the Stokes equations. The method uses polynomials of degree k for all the c...
The aim of this paper is to achieve seamless image stitching for eliminating obvious visual artifact caused by severe intensity discrepancy, image distortion and structure misalig...