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A generalized Gaussian image model for edge-preserving MAP estimation

by Charles Bouman, Ken Sauer - IEEE Trans. on Image Processing , 1993
"... Absfrucf- We present a Markov random field model which allows realistic edge modeling while providing stable maximum a posteriori MAP solutions. The proposed model, which we refer to as a generalized Gaussian Markov random field (GGMRF), is named for its similarity to the generalized Gaussian distri ..."
Abstract - Cited by 301 (37 self) - Add to MetaCart
Absfrucf- We present a Markov random field model which allows realistic edge modeling while providing stable maximum a posteriori MAP solutions. The proposed model, which we refer to as a generalized Gaussian Markov random field (GGMRF), is named for its similarity to the generalized Gaussian

An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is

by Johnathan M. Bardsley†‡and John Goldes - Poisson, accepted in the SIAM Journal on Scientific Computing
"... Abstract. In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-log Poisson likelihood function for data fitting. (The fact that application scientists in both astronomical and ..."
Abstract - Cited by 5 (4 self) - Add to MetaCart
constrained, convex optimization problems that arise when the negative-log Poisson likelihood is used are therefore more challenging than when least squares is the fit-to-data function. Edge preserving deblurring and denoising has long been a problem of keen interest in the image processing community. While

Exact distribution of edge-preserving MAP estimators for linear signal models with Gaussian measurement noise

by Jeffrey A. Fessler, Wei Biao Wu - IEEE Transactions on image processing , 2000
"... Abstract—We derive the exact statistical distribution of maximum a posteriori (MAP) estimators having edge-preserving non-Gaussian priors. Such estimators have been widely advocated for image restoration and reconstruction problems. Previous investigations of these image recovery methods have been p ..."
Abstract - Cited by 11 (2 self) - Add to MetaCart
Abstract—We derive the exact statistical distribution of maximum a posteriori (MAP) estimators having edge-preserving non-Gaussian priors. Such estimators have been widely advocated for image restoration and reconstruction problems. Previous investigations of these image recovery methods have been

A solution to the simultaneous localization and map building (SLAM) problem

by M. W. M. Gamini Dissanayake, Paul Newman, Steven Clark, Hugh F. Durrant-whyte, M. Csorba - IEEE Transactions on Robotics and Automation , 2001
"... Abstract—The simultaneous localization and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle ..."
Abstract - Cited by 505 (30 self) - Add to MetaCart
location. Starting from the estimation-theoretic foundations of this problem developed in [1]–[3], this paper proves that a solution to the SLAM problem is indeed possible. The underlying structure of the SLAM problem is first elucidated. A proof that the estimated map converges monotonically to a relative

FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem

by Michael Montemerlo, Sebastian Thrun, Daphne Koller, Ben Wegbreit - In Proceedings of the AAAI National Conference on Artificial Intelligence , 2002
"... The ability to simultaneously localize a robot and accurately map its surroundings is considered by many to be a key prerequisite of truly autonomous robots. However, few approaches to this problem scale up to handle the very large number of landmarks present in real environments. Kalman filter-base ..."
Abstract - Cited by 599 (10 self) - Add to MetaCart
The ability to simultaneously localize a robot and accurately map its surroundings is considered by many to be a key prerequisite of truly autonomous robots. However, few approaches to this problem scale up to handle the very large number of landmarks present in real environments. Kalman filter

A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots

by Sebastian Thrun, Wolfram Burgard, Dieter Fox, Henry Hexmoor, Maja Mataric - Machine Learning , 1998
"... . This paper addresses the problem of building large-scale geometric maps of indoor environments with mobile robots. It poses the map building problem as a constrained, probabilistic maximum-likelihood estimation problem. It then devises a practical algorithm for generating the most likely map from ..."
Abstract - Cited by 483 (43 self) - Add to MetaCart
. This paper addresses the problem of building large-scale geometric maps of indoor environments with mobile robots. It poses the map building problem as a constrained, probabilistic maximum-likelihood estimation problem. It then devises a practical algorithm for generating the most likely map from

Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images.

by Stuart Geman , Donald Geman - IEEE Trans. Pattern Anal. Mach. Intell. , 1984
"... Abstract-We make an analogy between images and statistical mechanics systems. Pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a lattice-like physical system. The assignment of an energy function in the physical system determines its Gibbs di ..."
Abstract - Cited by 5126 (1 self) - Add to MetaCart
system isolates low energy states ("annealing"), or what is the same thing, the most probable states under the Gibbs distribution. The analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations. The result

Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching

by Sergey Melnik, Hector Garcia-molina, Erhard Rahm , 2002
"... Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs (sch ..."
Abstract - Cited by 592 (12 self) - Add to MetaCart
(schemas, catalogs, or other data structures) as input, and produces as output a mapping between corresponding nodes of the graphs. Depending on the matching goal, a subset of the mapping is chosen using filters. After our algorithm runs, we expect a human to check and if necessary adjust the results. As a

Iterative point matching for registration of free-form curves and surfaces

by Zhengyou Zhang , 1994
"... A heuristic method has been developed for registering two sets of 3-D curves obtained by using an edge-based stereo system, or two dense 3-D maps obtained by using a correlation-based stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in ma ..."
Abstract - Cited by 660 (8 self) - Add to MetaCart
A heuristic method has been developed for registering two sets of 3-D curves obtained by using an edge-based stereo system, or two dense 3-D maps obtained by using a correlation-based stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately

Real-time human pose recognition in parts from single depth images

by Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, Andrew Blake - IN CVPR , 2011
"... We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler p ..."
Abstract - Cited by 568 (17 self) - Add to MetaCart
We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler
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