Introduction to the special section on graph algorithms in computer vision

Introduction to the Special Section on Graph Algorithms in Computer Vision

setting with solid theoretical underpinnings and also permits access to the full arsenal of graph algorithms developed in computer science and operations research. Graph-theoretic problems which have proven to be relevant to computer vision include maximum flow, minimum spanning tree, maximum clique, shortest path, maximal common subtree/subgraph, etc. In addition, a number of fundamental techn...

Introduction to the Special Section on In-Vehicle Computer Vision Systems

Guest Editors' Introduction to the Special Section on Graphical Models in Computer Vision

THE last 10 years have witnessed rapid growth in the popularity of graphical models, most notably Bayesian networks, as a tool for representing, learning, and computing complex probability distributions. Graphical models provide an explicit representation of the statistical dependencies between the components of a complex probability model, effectively marrying probability theory and graph theo...

Guest Editors' Introduction: Special Section on Higher Order Graphical Models in Computer Vision

MANY tasks in computer vision, including low-level ones such as image segmentation and stereo estimation, as well as high-level ones such as object recognition and scene understanding, have been modelled as discrete labelling problems. To solve these problems discrete optimization has emerged as an indispensable tool over the last two decades. It is now a routine process to write an explicit en...

Introduction to the Special Section on Epigenetics.

Epigenetics provides the opportunity to revolutionize our understanding of the role of genetics and the environment in explaining human behavior, although the use of epigenetics to study human behavior is just beginning. In this introduction, the authors present the basics of epigenetics in a way that is designed to make this exciting field accessible to a wide readership. The authors describe ...