Abstract. A dynamic visual search framework based mainly on innerscene similarity is proposed. Algorithms as well as measures quantifying the difficulty of search tasks are suggest...
Abstract. Segmentation and blind restoration are both classical problems, that are known to be difficult and have attracted major research efforts. This paper shows that the two pr...
Abstract. We propose a variational framework for the integration multiple competing shape priors into level set based segmentation schemes. By optimizing an appropriate cost functi...
Daniel Cremers, Nir A. Sochen, Christoph Schnö...
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Abstract. We formulate a robust method using Expectation Maximization (EM) to address the problem of dense photometric stereo. Previous approaches using Markov Random Fields (MRF) ...