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Haar LBP Gabor Jet boosting Gabor Jet
 

Summary:  Boosting
1
boosting

Haar LBP Gabor Jet boosting
LBP Haar
Gabor Jet
boosting
TP391
Demographical classification by shape free texture and boosting
learning
Abstract In this paper, a gender and age classification method, in which age is classified into four
classes: child, youth, midlife and agedness, based on shape free texture and boosting learning is
introduced. After a face is detected, face alignment extracts 88 facial landmarks by which the face
image is normalized to a shape free texture. Further more, three kinds of local feature, Haar like feature,
LBP histogram and Gabor jet are extracted from the shape free texture; and boosting learning method
is used for training classifiers. Through experiment it is shown that, LBP histogram can be used for
robust recognition of children and old people, Haar like feature is more efficient for discriminating
young and middle aged people, and Gabor Jet fits for gender classification best.
Keywords: demographical classification, boosting, face image processing

  

Source: Ai, Haizhou - Department of Computer Science and Technology, Tsinghua University

 

Collections: Computer Technologies and Information Sciences