Paper Info
Title
Facial expression recognition based on boostingtree
Abstract
In recent years, facial expression recognition has become an active research area that finds potential applications in the fields such as images processing and pattern recognition, and it plays a very important role in the applications of human-computer interfaces and human emotion analysis. This paper proposes an algorithm called BoostingTree, which is based on the conventional Adaboost and uses tree-structure to convert seven facial expressions to six binary problems, and also presents a novel method to compute projection matrix based on Principal Component Analysis (PCA). In this novel method, a block-merger combination is designed to solve the “data disaster” problem due to the combination of eigenvectors. In the experiment, we construct the weak classifiers set based on this novel method. The weak classifiers selected from the above set by Adaboost are combined into strong classifier to be as node classifier of one level of the tree structure. N-level tree structure built by BoostingTree can effectively solve multiclass problem such as facial expression recognition
Year
DOI
Venue
2006
10.1007/11760023_12
ISNN (2)
Keywords
Field
DocType
novel method,pattern recognition,multiclass problem,facial expression,weak classifier,n-level tree structure,conventional adaboost,block-merger combination,facial expression recognition,binary problem,human computer interface,principal component analysis,eigenvectors,tree structure
AdaBoost,Pattern recognition,Computer science,Image processing,Supervised learning,Facial expression,Tree structure,Artificial intelligence,Classifier (linguistics),Artificial neural network,Machine learning,Principal component analysis
Conference
Volume
ISSN
ISBN
3972
0302-9743
3-540-34437-3
Citations 
PageRank 
References 
1
0.36
6
Authors
5
Name
Order
Citations
PageRank
Ning Sun111813.20
Wenming Zheng2124080.70
Changyin Sun32002157.17
Cairong Zou441527.19
Li Zhao538027.36