TY - GEN
T1 - Wrinkle feature-based skin age estimation scheme
AU - Kim, Kyungrok
AU - Choi, Young Hwan
AU - Hwang, Eenjun
PY - 2009
Y1 - 2009
N2 - With the rapid deployment of information technology and the availability of cheap yet high performance image capturing devices, new types of healthcare services such as self-diagnosis and treatment have become possible. Skin is the outer layer of the human body and has long attracted a great deal of attention, since its appearance conveys useful information on the health condition of the subject. In this paper, we propose a skin age estimation scheme based on its wrinkle features such as length, width and depth, which represents the physical condition of skin statistically and quantitatively. We collected wrinkle features and personal data from various subjects, including age and gender, and constructed the ground truth in consultation with dermatologists. For the estimation, we used a non-linear, multi-class SVM (Support Vector Machine). Via extensive experiments on our prototype system, we show that our scheme achieves a reasonable accuracy.
AB - With the rapid deployment of information technology and the availability of cheap yet high performance image capturing devices, new types of healthcare services such as self-diagnosis and treatment have become possible. Skin is the outer layer of the human body and has long attracted a great deal of attention, since its appearance conveys useful information on the health condition of the subject. In this paper, we propose a skin age estimation scheme based on its wrinkle features such as length, width and depth, which represents the physical condition of skin statistically and quantitatively. We collected wrinkle features and personal data from various subjects, including age and gender, and constructed the ground truth in consultation with dermatologists. For the estimation, we used a non-linear, multi-class SVM (Support Vector Machine). Via extensive experiments on our prototype system, we show that our scheme achieves a reasonable accuracy.
KW - Health care
KW - SVM classifier
KW - Skin age
KW - Wrinkle features
UR - http://www.scopus.com/inward/record.url?scp=70449574592&partnerID=8YFLogxK
U2 - 10.1109/ICME.2009.5202721
DO - 10.1109/ICME.2009.5202721
M3 - Conference contribution
AN - SCOPUS:70449574592
SN - 9781424442911
T3 - Proceedings - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009
SP - 1222
EP - 1225
BT - Proceedings - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009
T2 - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009
Y2 - 28 June 2009 through 3 July 2009
ER -