DocumentCode
131416
Title
A Novel Face Detection Algorithm Based on PCA and Adaboost
Author
Liu Shuang
Author_Institution
Qingyuan Polytech., Qingyuan, China
fYear
2014
fDate
10-11 Jan. 2014
Firstpage
38
Lastpage
41
Abstract
This paper studies the feature based face detection algorithm. Based on the principal component analysis, feature vector space is extracted to construct weak classifier. Combined with Adaboost algorithm to construct the strong classifier, an algorithm for face detection is presented. The performance of the algorithm is tested based on MIT+CMU face database, the results show that the algorithm in the running time and detection accuracy is significantly better than the algorithm based on neural network and support vector machine algorithm.
Keywords
face recognition; learning (artificial intelligence); principal component analysis; Adaboost algorithm; MIT+CMU face database; PCA; face detection algorithm; feature vector space; principal component analysis; Algorithm design and analysis; Classification algorithms; Face; Face detection; Feature extraction; Image color analysis; Principal component analysis; Adaboost; Face Detection; Principal Component Analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
Conference_Location
Zhangjiajie
Print_ISBN
978-1-4799-3434-8
Type
conf
DOI
10.1109/ICMTMA.2014.16
Filename
6802631
Link To Document