In this paper, we propose a robust technique that integrates spatial and temporal information for consistent recovery of the endocardium. To account for the low image quality we in...
We introduce a novel data-driven mean-shift belief propagation
(DDMSBP) method for non-Gaussian MRFs, which
often arise in computer vision applications. With the aid
of scale sp...
This paper introduces a novel method of visual learning based on Genetic Programming, which evolves a population of individuals (image analysis programs) that process attributed v...
Abstract. In this paper, we present a novel successive relaxation linear programming scheme for solving the important class of consistent labeling problems for which an L1 metric i...
We reduce transmission bandwidth and memory space for images by factoring their repeated content. A transform map and a condensed epitome are created such that all image blocks ca...