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» Boosting Object Detection Using Feature Selection
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CVPR
2007
IEEE
14 years 9 months ago
Eigenboosting: Combining Discriminative and Generative Information
A major shortcoming of discriminative recognition and detection methods is their noise sensitivity, both during training and recognition. This may lead to very sensitive and britt...
Helmut Grabner, Peter M. Roth, Horst Bischof
PRL
2006
180views more  PRL 2006»
13 years 7 months ago
MutualBoost learning for selecting Gabor features for face recognition
This paper describes an improved boosting algorithm, the MutualBoost algorithm, and its application in developing a fast and robust Gabor feature based face recognition system. Th...
LinLin Shen, Li Bai
CIRA
2007
IEEE
274views Robotics» more  CIRA 2007»
14 years 1 months ago
Adaptive Object Tracking using Particle Swarm Optimization
—This paper presents an automatic object detection and tracking algorithm by using particle swarm optimization (PSO) based method, which is a searching algorithm inspired by the ...
Yuhua Zheng, Yan Meng
ICMCS
2009
IEEE
146views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Boosting multi-modal camera selection with semantic features
In this work semantic features are used to improve the results of the camera selection. These semantic features are group action, person action and person speaking. For this purpo...
Benedikt Hörnler, Dejan Arsic, Björn Sch...
ICPR
2006
IEEE
14 years 8 months ago
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification
Band ratios have many useful applications in hyperspectral image analysis. While optimal ratios have been chosen empirically in previous research, we propose a principled algorith...
Antonio Robles-Kelly, Nianjun Liu, Terry Caelli, Z...