Title :
Face classification by a random forest
Author :
Kouzani, A.Z. ; Nahavandi, S. ; Khoshmanesh, K.
Author_Institution :
Deakin Univ., Geelong
fDate :
Oct. 30 2007-Nov. 2 2007
Abstract :
This paper presents a random forest-based face image classification method. The random forest is an ensemble learning method that grows many classification trees. Each tree gives a classification. The forest selects the classification that has the most votes. Three experiments are performed. The random forest-based method together with several existing approaches are trained and evaluated. The experimental results are presented and discussed.
Keywords :
face recognition; image classification; random processes; classification trees; ensemble learning; face classification; image classification; random forest; Bagging; Boosting; Classification tree analysis; Face recognition; Image classification; Independent component analysis; Learning systems; Predictive models; Support vector machines; Voting;
Conference_Titel :
TENCON 2007 - 2007 IEEE Region 10 Conference
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-1272-3
Electronic_ISBN :
978-1-4244-1272-3
DOI :
10.1109/TENCON.2007.4428937