Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
A DRAFT computer vision book by Prof. Richard Szeliski. The book reflects the author's wide experience in practical computer vision algorithms that he has developed while work...
Ubiquitous computing is unusual amongst technological research arenas. Most areas of computer science research, such as programming language implementation, distributed operating s...
The traditional goal of computer vision, to reconstruct, or recover properties of, the scene has recently been challenged by advocates of a new purposive approach in which the vis...
Michael J. Black, Yiannis Aloimonos, Christopher M...
This paper presents a novel approach that represents an image or a set of images using a nonorthogonal binary subspace (NBS) spanned by boxlike base vectors. These base vectors po...