An
Efficient Age Estimation System with Facial Makeover Images Based on Key Points
Selection
Tamilb
Vairavan1 and Kaliyaperumal Vani2
1Department of Electronics and
Instrumentation, R.M.K Engineering College, India
2Department of Information Science
and Technology College of Engineering, Anna University, India
Abstract: Age is one of the essential factors
in establishing the identity of the person. Estimation of the human age is a
procedure adopted by anthropologists, archaeologists and forensic scientists.
Compared with other cognition problems, age estimation from face images is
still very challenging. Predicting and estimating the age from facial images
with makeup is an interesting task in digital entertainment. Estimating age
from a facial image is an intriguing and exigent task. Aging changes both shape
as well as texture and it is an irreversible, uncontrollable and personalized.
The efficiency of the age estimation system degrades with respect to facial
makeover. The main objective of this research is to estimate the age of a human
from the facial image with makeup. Initially, the face image will be normalized
by employing a face detection algorithm. After detecting the face exactly, we
have extracted the unique features (key points) from the images such as
texture, shape and regions. Estimating the age of a person with different makeovers
is not an easy task. To overcome this difficulty, we have to identify the
uniqueness of each image of a same person. The eye part does not change
whatever the person having the makeup. So the eyes are same for the person with
different makeover. For region area or key points, the eye portion will be
segmented from the detected face image. The shape feature can be extracted by Active
Appearance Model (AAM). Finally, based on the feature library, the image can be
classified under a particular age group using Artificial Neural Network (ANN).
After the classification the age can be predicted. The proposed approach will
be implemented in MATLAB and planned to be evaluated using various facial
makeover images.
Keywords: Age estimation system, AAM, ANN,
LGXP.
Received July 1, 2013; accepted March 20, 2014