DocumentCode
2605490
Title
Face Detection in Complex Background Using AdaBoost Algorithm
Author
Guanglei Sheng ; Wenze Li
Author_Institution
Zhengzhou Shengda Coll. of Econ.&Trade Manage., Zhengzhou, China
fYear
2012
fDate
21-23 April 2012
Firstpage
149
Lastpage
154
Abstract
This paper has studied one kind based on rectangle features face detection technology. The first use of a fixed size training set training out of each rectangle features corresponding to the weak classifier, the weak classifier selection, made some improvement. Using AdaBoost algorithm to train the weak classifier, we get a strong classifier. In the end, we make strong classifier construction into a cascade structure of a human face detector, the experimental results show that the detector can quickly and accurately detect the human face images.
Keywords
face recognition; feature extraction; image classification; learning (artificial intelligence); object detection; AdaBoost algorithm; complex background; face detection; fixed size training set; human face detector; rectangle features; weak classifier selection; Classification algorithms; Face; Face detection; Feature extraction; Humans; Pattern recognition; Training; face detection; integral image; rectangle feature; skin color segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Internet Computing for Science and Engineering (ICICSE), 2012 Sixth International Conference on
Conference_Location
Henan
Print_ISBN
978-1-4673-1683-5
Type
conf
DOI
10.1109/ICICSE.2012.23
Filename
6239738
Link To Document