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PRL
2008
96views more  PRL 2008»
13 years 3 months ago
Outlier rejection for cameras on intelligent vehicles
This paper proposes an algorithm for rejecting false matches (known as outliers) in image pairs acquired with automobile-mounted cameras. Many intelligent vehicle applications req...
Jae Kyu Suhr, Ho Gi Jung, Kwanghyuk Bae, Jaihie Ki...
PAMI
2008
200views more  PAMI 2008»
13 years 3 months ago
Principal Component Analysis Based on L1-Norm Maximization
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
Nojun Kwak
KAIS
2006
77views more  KAIS 2006»
13 years 3 months ago
Finding centric local outliers in categorical/numerical spaces
Outlier detection techniques are widely used in many applications such as credit card fraud detection, monitoring criminal activities in electronic commerce, etc. These application...
Jeffrey Xu Yu, Weining Qian, Hongjun Lu, Aoying Zh...
CSDA
2006
108views more  CSDA 2006»
13 years 3 months ago
Repeated median and hybrid filters
Standard median filters preserve abrupt shifts (edges) and remove impulsive noise (outliers) from a constant signal but they deteriorate in trend periods. Finite impulse response ...
Roland Fried, Thorsten Bernholt, Ursula Gather
BMCBI
2006
187views more  BMCBI 2006»
13 years 3 months ago
Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Harvey J. Motulsky, Ronald E. Brown
DCG
2008
93views more  DCG 2008»
13 years 3 months ago
Robust Shape Fitting via Peeling and Grating Coresets
Let P be a set of n points in Rd . A subset S of P is called a (k, )-kernel if for every direction, the direction width of S -approximates that of P, when k "outliers" c...
Pankaj K. Agarwal, Sariel Har-Peled, Hai Yu
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 3 months ago
Robust Matrix Decomposition with Outliers
Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...
Daniel Hsu, Sham M. Kakade, Tong Zhang
CGF
2010
111views more  CGF 2010»
13 years 3 months ago
Density-based Outlier Rejection in Monte Carlo Rendering
The problem of noise in Monte-Carlo rendering arising from estimator variance is well-known and well-studied. In this work, we concentrate on identifying individual light paths as...
Christopher DeCoro, Tim Weyrich, Szymon Rusinkiewi...
AMCS
2008
146views Mathematics» more  AMCS 2008»
13 years 3 months ago
Fault Detection and Isolation with Robust Principal Component Analysis
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
Yvon Tharrault, Gilles Mourot, José Ragot, ...
AMC
2007
80views more  AMC 2007»
13 years 3 months ago
A dynamic generating graphical model for point-sets matching
This paper presents a new dynamic generating graphical model for point-sets matching. The existing algorithms on graphical models proved to be quite robust to noise but are suscep...
Xuan Zhao, Shengjin Wang, Xiaoqing Ding