Sciweavers

437 search results - page 14 / 88
» Face detection using large margin classifiers
Sort
View
ICPR
2008
IEEE
14 years 10 months ago
A method of feature selection using contribution ratio based on boosting
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
Masamitsu Tsuchiya, Hironobu Fujiyoshi
NIPS
2001
13 years 11 months ago
Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
This paper develops a new approach for extremely fast detection in domains where the distribution of positive and negative examples is highly skewed (e.g. face detection or databa...
Paul A. Viola, Michael J. Jones
CVPR
2001
IEEE
14 years 11 months ago
Learning Representative Local Features for Face Detection
This paper describes a face detection approach via learning local features. The key idea is that local features, being manifested by a collection of pixels in a local region, are ...
Xiangrong Chen, Lie Gu, Stan Z. Li, HongJiang Zhan...
MIR
2004
ACM
101views Multimedia» more  MIR 2004»
14 years 3 months ago
Leveraging face recognition technology to find and organize photos
With digital still cameras, users can easily collect thousands of photos. We have created a photo management application with the goal of making photo organization and browsing si...
Andreas Girgensohn, John Adcock, Lynn Wilcox
DIS
2006
Springer
14 years 1 months ago
Incremental Algorithm Driven by Error Margins
Incremental learning is an approach to deal with the classification task when datasets are too large or when new examples can arrive at any time. One possible approach uses concent...
Gonzalo Ramos-Jiménez, José del Camp...