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IWBRS
2005
Springer
168views Biometrics» more  IWBRS 2005»
14 years 1 months ago
Gabor Feature Selection for Face Recognition Using Improved AdaBoost Learning
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
CVPR
2004
IEEE
14 years 9 months ago
Asymmetrically Boosted HMM for Speech Reading
Speech reading, also known as lip reading, is aimed at extracting visual cues of lip and facial movements to aid in recognition of speech. The main hurdle for speech reading is th...
Pei Yin, Irfan A. Essa, James M. Rehg
IJCAI
2007
13 years 9 months ago
Training Conditional Random Fields Using Virtual Evidence Boosting
While conditional random fields (CRFs) have been applied successfully in a variety of domains, their training remains a challenging task. In this paper, we introduce a novel trai...
Lin Liao, Tanzeem Choudhury, Dieter Fox, Henry A. ...
ICIP
2010
IEEE
13 years 5 months ago
Fast object detection using boosted co-occurrence histograms of oriented gradients
Co-occurrence histograms of oriented gradients (CoHOG) are powerful descriptors in object detection. In this paper, we propose to utilize a very large pool of CoHOG features with ...
Haoyu Ren, Cher-Keng Heng, Wei Zheng, Luhong Liang...
ICCCN
2007
IEEE
13 years 7 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