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ICCCN
2007
IEEE
14 years 12 months ago
Online Selection of Tracking Features using AdaBoost
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
Ying-Jia Yeh, Chiou-Ting Hsu
CVPR
2012
IEEE
13 years 2 months ago
Boosting algorithms for simultaneous feature extraction and selection
The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...
Mohammad J. Saberian, Nuno Vasconcelos
ECCV
2008
Springer
16 years 1 months ago
Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images
Abstract. We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose f...
Ryuzo Okada, Stefano Soatto
CVPR
2004
IEEE
16 years 1 months ago
Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection
We consider the problem of detecting a large number of different object classes in cluttered scenes. Traditional approaches require applying a battery of different classifiers to ...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
ICCV
1999
IEEE
15 years 4 months ago
Motion Segmentation based on Factorization Method and Discriminant Criterion
A motion segmentation algorithm based on factorization method and discriminant criterion is proposed. This method uses a feature with the most useful similarities for grouping, se...
Naoyuki Ichimura