Results 11  20
of
157,101
A Survey of Computer VisionBased Human Motion Capture
 Computer Vision and Image Understanding
, 2001
"... A comprehensive survey of computer visionbased 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 508 (14 self)
 Add to MetaCart
A comprehensive survey of computer visionbased 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
DecisionTheoretic Planning: Structural Assumptions and Computational Leverage
 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 510 (4 self)
 Add to MetaCart
related methods, showing how they provide a unifying framework for modeling many classes of planning problems studied in AI. It also describes structural properties of MDPs that, when exhibited by particular classes of problems, can be exploited in the construction of optimal or approximately optimal policies
Functional discovery via a compendium of expression profiles. Cell 102:109
, 2000
"... have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of ..."
Abstract

Cited by 537 (8 self)
 Add to MetaCart
have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of
A fast and high quality multilevel scheme for partitioning irregular graphs
 SIAM JOURNAL ON SCIENTIFIC COMPUTING
, 1998
"... Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then uncoarsen it to construct a partition for the original graph [Bui and Jones, Proc. ..."
Abstract

Cited by 1173 (16 self)
 Add to MetaCart
Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then uncoarsen it to construct a partition for the original graph [Bui and Jones, Proc.
Finding community structure in networks using the eigenvectors of matrices
, 2006
"... We consider the problem of detecting communities or modules in networks, groups of vertices with a higherthanaverage density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as “modularity ” over possible div ..."
Abstract

Cited by 500 (0 self)
 Add to MetaCart
We consider the problem of detecting communities or modules in networks, groups of vertices with a higherthanaverage density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as “modularity ” over possible
Just Relax: Convex Programming Methods for Identifying Sparse Signals in Noise
, 2006
"... This paper studies a difficult and fundamental problem that arises throughout electrical engineering, applied mathematics, and statistics. Suppose that one forms a short linear combination of elementary signals drawn from a large, fixed collection. Given an observation of the linear combination that ..."
Abstract

Cited by 496 (2 self)
 Add to MetaCart
. This paper studies a method called convex relaxation, which attempts to recover the ideal sparse signal by solving a convex program. This approach is powerful because the optimization can be completed in polynomial time with standard scientific software. The paper provides general conditions which ensure
Volume of Fluid (VOF) Method for the Dynamics of Free Boundaries,” Los Alamos Scientific Laboratory report
"... Several methods have been previously used to approximate free boundaries in tinitedifference numerical simulations. A simple, but powerful, method is described that is based on the concept of a fractional volume of fluid (VOF). This method is shown to be more flexible and efftcient than other method ..."
Abstract

Cited by 544 (2 self)
 Add to MetaCart
Several methods have been previously used to approximate free boundaries in tinitedifference numerical simulations. A simple, but powerful, method is described that is based on the concept of a fractional volume of fluid (VOF). This method is shown to be more flexible and efftcient than other
Improved methods for building protein models in electron density maps and the location of errors in these models. Acta Crystallogr. sect
 A
, 1991
"... Map interpretation remains a critical step in solving the structure of a macromolecule. Errors introduced at this early stage may persist throughout crystallographic refinement and result in an incorrect structure. The normally quoted crystallographic residual is often a poor description for the q ..."
Abstract

Cited by 1016 (9 self)
 Add to MetaCart
Map interpretation remains a critical step in solving the structure of a macromolecule. Errors introduced at this early stage may persist throughout crystallographic refinement and result in an incorrect structure. The normally quoted crystallographic residual is often a poor description for the quality of the model. Strategies and tools are described that help to alleviate this problem. These simplify the modelbuilding process, quantify the goodness of fit of the model on a perresidue basis and locate possible errors in peptide and sidechain conformations.
Dynamical densitymatrix renormalization group
"... The dynamical densitymatrix renormalization group (DDMRG) method is a numerical technique for calculating the zerotemperature dynamical properties in lowdimensional quantum manybody systems. For the onedimensional Hubbard model and its extensions, DDMRG allows for accurate calculations of these ..."
Abstract
 Add to MetaCart
The dynamical densitymatrix renormalization group (DDMRG) method is a numerical technique for calculating the zerotemperature dynamical properties in lowdimensional quantum manybody systems. For the onedimensional Hubbard model and its extensions, DDMRG allows for accurate calculations
Bundle Adjustment  A Modern Synthesis
 VISION ALGORITHMS: THEORY AND PRACTICE, LNCS
, 2000
"... This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics c ..."
Abstract

Cited by 555 (12 self)
 Add to MetaCart
This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics
Results 11  20
of
157,101