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CVPR
2007
IEEE
15 years 3 months ago
Object Classification in Visual Surveillance Using Adaboost
In this paper, we present a method of object classification within the context of Visual Surveillance. Our goal is the classification of tracked objects into one of the two classe...
John-Paul Renno, Dimitrios Makris, Graeme A. Jones
PRL
2008
213views more  PRL 2008»
14 years 11 months ago
Boosting recombined weak classifiers
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the comb...
Juan José Rodríguez, Jesús Ma...
AIPRF
2007
15 years 1 months ago
Evaluation of Different Approaches to Training a Genre Classifier
This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected ba...
Vedrana Vidulin, Mitja Lustrek, Matjaz Gams
ICPR
2010
IEEE
14 years 12 months ago
Adaptive Incremental Learning with an Ensemble of Support Vector Machines
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin
IVC
2006
187views more  IVC 2006»
14 years 11 months ago
Dynamics of facial expression extracted automatically from video
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions, including AdaBoost, support vector mach...
Gwen Littlewort, Marian Stewart Bartlett, Ian R. F...