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» Learning Boosted Asymmetric Classifiers for Object Detection
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CVPR
2004
IEEE
14 years 9 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...
FGR
2004
IEEE
231views Biometrics» more  FGR 2004»
13 years 11 months ago
A Boosted Classifier Tree for Hand Shape Detection
The ability to detect a persons unconstrained hand in a natural video sequence has applications in sign language, gesture recognition and HCI. This paper presents a novel, unsuper...
Eng-Jon Ong, Richard Bowden
JRTIP
2010
137views more  JRTIP 2010»
13 years 2 months ago
Cascaded online boosting
In this paper, we propose a cascaded version of the online boosting algorithm to speed-up the execution time and guarantee real-time performance even when employing a large number ...
Ingrid Visentini, Lauro Snidaro, Gian Luca Foresti
CVPR
2007
IEEE
14 years 9 months ago
Learning Features for Tracking
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
Michael Grabner, Helmut Grabner, Horst Bischof
ICPR
2004
IEEE
14 years 8 months ago
Real-Time Face Detection Using Boosting in Hierarchical Feature Spaces
Boosting-basedmethods have recently led to the state-ofthe-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like featu...
Daniel Gatica-Perez, Dong Zhang, Stan Z. Li