Results 1  10
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392
Realtime human pose recognition in parts from single depth images
 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)
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perpixel classification problem. Our large and highly varied training dataset allows the classifier to estimate body parts invariant to pose, body shape, clothing, etc. Finally we generate confidencescored 3D proposals of several body joints by reprojecting the classification result and finding
Large Margin Classification Using the Perceptron Algorithm
 Machine Learning
, 1998
"... We introduce and analyze a new algorithm for linear classification which combines Rosenblatt 's perceptron algorithm with Helmbold and Warmuth's leaveoneout method. Like Vapnik 's maximalmargin classifier, our algorithm takes advantage of data that are linearly separable with large ..."
Abstract

Cited by 521 (2 self)
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We introduce and analyze a new algorithm for linear classification which combines Rosenblatt 's perceptron algorithm with Helmbold and Warmuth's leaveoneout method. Like Vapnik 's maximalmargin classifier, our algorithm takes advantage of data that are linearly separable
Hierarchically Classifying Documents Using Very Few Words
, 1997
"... The proliferation of topic hierarchies for text documents has resulted in a need for tools that automatically classify new documents within such hierarchies. Existing classification schemes which ignore the hierarchical structure and treat the topics as separate classes are often inadequate in text ..."
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Cited by 521 (8 self)
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classification where the there is a large number of classes and a huge number of relevant features needed to distinguish between them. We propose an approach that utilizes the hierarchical topic structure to decompose the classification task into a set of simpler problems, one at each node in the classification
Improved Boosting Algorithms Using Confidencerated Predictions
 MACHINE LEARNING
, 1999
"... We describe several improvements to Freund and Schapire’s AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each of their predictions. We give a simplified analysis of AdaBoost in this setting, and we show how this analysis can be used to find impr ..."
Abstract

Cited by 940 (26 self)
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out to be identical to one proposed by Kearns and Mansour. We focus next on how to apply the new boosting algorithms to multiclass classification problems, particularly to the multilabel case in which each example may belong to more than one class. We give two boosting methods for this problem, plus
A Survey on Image Classification Algorithm Based on Perpixel
"... Abstract—In this paper, we presents a literature survey on the various approaches used for classifying scenes which is mainly based on object in the given image. In scene classification, classification of images is an intricate process which is the necessity to classify, organize and access them usi ..."
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Cited by 1 (0 self)
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using an easy, faster and efficient way to achieve higher image accuracy within less execution time. The classification of images into semantic categories is an interesting and significant problem. Many different approaches have been proposed relating to object scene classification in the last few years
Multitask learning for classification with dirichlet process priors
 Journal of Machine Learning Research
, 2007
"... Multitask learning (MTL) is considered for logisticregression classifiers, based on a Dirichlet process (DP) formulation. A symmetric MTL (SMTL) formulation is considered in which classifiers for multiple tasks are learned jointly, with a variational Bayesian (VB) solution. We also consider an asy ..."
Abstract

Cited by 140 (12 self)
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with a simple Markov Chain Monte Carlo (MCMC) construction. Comparisons are also made to simpler approaches, such as singletask learning, pooling of data across tasks, and simplified approximations to DP. A comprehensive analysis of algorithm performance is addressed through consideration of two data
Selecting a Classification Method by CrossValidation
 Machine Learning
, 1993
"... If we lack relevant problemspecific knowledge, crossvalidation methods may be used to select a classification method empirically. We examine this idea here to show in what senses crossvalidation does and does not solve the selection problem. As illustrated empirically, crossvalidation may lead t ..."
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Cited by 88 (0 self)
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If we lack relevant problemspecific knowledge, crossvalidation methods may be used to select a classification method empirically. We examine this idea here to show in what senses crossvalidation does and does not solve the selection problem. As illustrated empirically, crossvalidation may lead
A.: Face detection with the modified census transform
 In: Proc. International Conference on Face and Gesture Recognition
, 2004
"... Illumination variation is a big problem in object recognition which usually requires a costly compensation prior to classification. It would be desirable to have an image to image transform which uncovers only the structure of an object for an efficient matching. In this context the contribution o ..."
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Cited by 115 (0 self)
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Illumination variation is a big problem in object recognition which usually requires a costly compensation prior to classification. It would be desirable to have an image to image transform which uncovers only the structure of an object for an efficient matching. In this context the contri
A Linear Programming Approach to Novelty Detection
, 2001
"... Novelty detection involves modeling the normal behaviour of a system hence enabling detection of any divergence from normality. It has potential applications in many areas such as detection of machine damage or highlighting abnormal features in medical data. One approach is to build a hypothesis ..."
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Cited by 89 (6 self)
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involves solution of a quadratic programming problem. In this paper we propose a simpler kernel method for estimating the support based on linear programming. The method is easy to implement and can learn large datasets rapidly. We demonstrate the method on medical and fault detection datasets. 1
On classification of dynamical rmatrices
 Math. Res. Letters
, 1998
"... Using the gauge transformations of the Classical Dynamical YangBaxter Equation introduced by P. Etingof and A. Varchenko in [EV], we reduce the classification of dynamical rmatrices on a commutative subalgebra l of a Lie algebra g to a purely algebraic problem under the assumption that l admits a ..."
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Cited by 28 (3 self)
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Using the gauge transformations of the Classical Dynamical YangBaxter Equation introduced by P. Etingof and A. Varchenko in [EV], we reduce the classification of dynamical rmatrices on a commutative subalgebra l of a Lie algebra g to a purely algebraic problem under the assumption that l admits a
Results 1  10
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392