Results 1 - 10 of 73,086

Light Field Rendering

by Marc Levoy , Pat Hanrahan , 1996
"... A number of techniques have been proposed for flying through scenes by redisplaying previously rendered or digitized views. Techniques have also been proposed for interpolating between views by warping input images, using depth information or correspondences between multiple images. In this paper, w ..."
Abstract - Cited by 1337 (22 self) - Add to MetaCart
- the light field. This function completely characterizes the flow of light through unobstructed space in a static scene with fixed illumination. We describe a

Inducing Features of Random Fields

by Stephen Della Pietra, Vincent Della Pietra, John Lafferty - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1997
"... We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the ..."
Abstract - Cited by 670 (10 self) - Add to MetaCart
We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing

Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions

by Xiaojin Zhu , Zoubin Ghahramani, John Lafferty - IN ICML , 2003
"... An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, with edge weights encoding the similarity between instances. The learning ..."
Abstract - Cited by 752 (14 self) - Add to MetaCart
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, with edge weights encoding the similarity between instances. The learning

The structure and function of complex networks

by M. E. J. Newman - SIAM REVIEW , 2003
"... Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, ..."
Abstract - Cited by 2600 (7 self) - Add to MetaCart
Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field

Relations and their basic properties

by Edmund Woronowicz - Journal of Formalized Mathematics , 1989
"... Summary. We define here: mode Relation as a set of pairs, the domain, the codomain, and the field of relation; the empty and the identity relations, the composition of relations, the image and the inverse image of a set under a relation. Two predicates, = and ⊆, and three functions, ∪, ∩ and \ are ..."
Abstract - Cited by 1060 (6 self) - Add to MetaCart
Summary. We define here: mode Relation as a set of pairs, the domain, the codomain, and the field of relation; the empty and the identity relations, the composition of relations, the image and the inverse image of a set under a relation. Two predicates, = and ⊆, and three functions

Sparse coding with an overcomplete basis set: a strategy employed by V1

by Bruno A. Olshausen, David J. Fieldt - Vision Research , 1997
"... The spatial receptive fields of simple cells in mammalian striate cortex have been reasonably well described physiologically and can be characterized as being localized, oriented, and ban@ass, comparable with the basis functions of wavelet transforms. Previously, we have shown that these receptive f ..."
Abstract - Cited by 958 (9 self) - Add to MetaCart
The spatial receptive fields of simple cells in mammalian striate cortex have been reasonably well described physiologically and can be characterized as being localized, oriented, and ban@ass, comparable with the basis functions of wavelet transforms. Previously, we have shown that these receptive

Factor Graphs and the Sum-Product Algorithm

by Frank R. Kschischang, Brendan J. Frey, Hans-Andrea Loeliger - IEEE TRANSACTIONS ON INFORMATION THEORY , 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
Abstract - Cited by 1791 (69 self) - Add to MetaCart
A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple

Rendering of Surfaces from Volume Data

by Marc Levoy - IEEE COMPUTER GRAPHICS AND APPLICATIONS , 1988
"... The application of volume rendering techniques to the display of surfaces from sampled scalar functions of three spatial dimensions is explored. Fitting of geometric primitives to the sampled data is not required. Images are formed by directly shading each sample and projecting it onto the picture ..."
Abstract - Cited by 875 (12 self) - Add to MetaCart
The application of volume rendering techniques to the display of surfaces from sampled scalar functions of three spatial dimensions is explored. Fitting of geometric primitives to the sampled data is not required. Images are formed by directly shading each sample and projecting it onto

A Survey of Computer Vision-Based Human Motion Capture

by Thomas B. Moeslund, Erik Granum - Computer Vision and Image Understanding , 2001
"... A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented. The focus is on a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition. Each ..."
Abstract - Cited by 515 (14 self) - Add to MetaCart
A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented. The focus is on a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition. Each

Decision-Theoretic Planning: Structural Assumptions and Computational Leverage

by Craig Boutilier, Thomas Dean, Steve Hanks - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH , 1999
"... Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions and perspectives ..."
Abstract - Cited by 515 (4 self) - Add to MetaCart
Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions
Results 1 - 10 of 73,086