Age estimation using active appearance model combining with local texture features

Chunhua Xie; Zhenming Peng; Lingbing Peng; Yang Yong

doi:10.1117/12.981748

30 November 2012 Age estimation using active appearance model combining with local texture features

Chunhua Xie, Zhenming Peng, Lingbing Peng, Yang Yong

Proceedings Volume 8558, Optoelectronic Imaging and Multimedia Technology II; 85581E (2012) https://doi.org/10.1117/12.981748
Event: Photonics Asia, 2012, Beijing, China

Abstract

In this paper, a novel age estimation method by using active appearance model (AAM) combining with local texture feature is presented, which overcomes the drawbacks of the AAM. Use the multi-scale local binary patterns (MLBP) as the local texture descriptors to get the rotation invariant texture features. Build the combined AAM model using MLBP features. In this way, both global face features and local texture features are used. The support vector regression (SVR) is used to estimate the facial age. The face aging data set FG-NET is used. Experimental results demonstrate the AAM combined MLBP method performing a lower mean-absolute error (MAE) and high accuracy of estimation comparing to other method results.

Citation Download Citation

Chunhua Xie, Zhenming Peng, Lingbing Peng, and Yang Yong "Age estimation using active appearance model combining with local texture features", Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85581E (30 November 2012); https://doi.org/10.1117/12.981748

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available