A hybrid approach of AdaBoost and Artificial Neural Network for detecting human faces

Author

Le, Thai Hoang ; Bui, Len Tien

Author_Institution

Dept. of Comput. Sci., HCMC Univ. of Natural Sci., Ho Chi Minh City

fYear

2008

fDate

13-17 July 2008

Firstpage

79

Lastpage

85

Abstract

The human face image recognition is one of the prominent problems at present. Recognizing human faces correctly will aid some fields such as national defense and person verification. One of the most vital processing of recognizing face images is to detect human faces in the images. Some approaches have been used to detect human faces. However, they still have some limitations. In the paper, we will consider some popular methods, AdaBoost, artificial neural network (ANN) etc., for detecting human faces. Then we will propose a hybrid model of combining AdaBoost and artificial neural network to solve the process efficiently. The system which was build from the proposed model has been conducted on database CalTech. The recognition correctness is more than 96%. It shows the feasibility of the proposed model.

Keywords

face recognition; neural nets; object detection; AdaBoost; artificial neural network; human face detection; human face image recognition; national defense; person verification; Artificial neural networks; Computer networks; Face detection; Face recognition; Hidden Markov models; Humans; Image databases; Image recognition; Learning systems; Machine learning; AdaBoost; Neural Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Research, Innovation and Vision for the Future, 2008. RIVF 2008. IEEE International Conference on

Conference_Location

Ho Chi Minh City

Print_ISBN

978-1-4244-2379-8

Electronic_ISBN

978-1-4244-2380-4

Type

conf

DOI

10.1109/RIVF.2008.4586336

Filename

4586336