TY - GEN
T1 - Image-based age-group classification design using facial features
AU - Chen, Yi Wen
AU - Han, Meng Ju
AU - Song, Kai-Tai
AU - Ho, Yu Lun
PY - 2010/10/11
Y1 - 2010/10/11
N2 - Image recognition of a user plays an important role in designing intelligent and interactive behaviors for a domestic or service robot. In this paper, an image-based age-group classification method is proposed to estimate three levels of age groups, namely child, adult and the elderly. After face detection from the acquired image frame, human facial area is extracted and 52 feature points are located by using Lucas-Kanade image alignment method. These feature points and corresponding located facial area are used to build an active appearance model (AAM). After facial image warping, the texture features are sent to a support vector machine (SVM) to estimate the level of age group. In the experimental results, the average recognition rate of the proposed method is 87%. It will improve the interaction capability of robot in a friendly manner.
AB - Image recognition of a user plays an important role in designing intelligent and interactive behaviors for a domestic or service robot. In this paper, an image-based age-group classification method is proposed to estimate three levels of age groups, namely child, adult and the elderly. After face detection from the acquired image frame, human facial area is extracted and 52 feature points are located by using Lucas-Kanade image alignment method. These feature points and corresponding located facial area are used to build an active appearance model (AAM). After facial image warping, the texture features are sent to a support vector machine (SVM) to estimate the level of age group. In the experimental results, the average recognition rate of the proposed method is 87%. It will improve the interaction capability of robot in a friendly manner.
KW - Active appearance model
KW - Age group estimation
KW - Facial warping
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=77957590029&partnerID=8YFLogxK
U2 - 10.1109/ICSSE.2010.5551744
DO - 10.1109/ICSSE.2010.5551744
M3 - Conference contribution
AN - SCOPUS:77957590029
SN - 9781424464746
T3 - 2010 International Conference on System Science and Engineering, ICSSE 2010
SP - 548
EP - 552
BT - 2010 International Conference on System Science and Engineering, ICSSE 2010
Y2 - 1 July 2010 through 3 July 2010
ER -