PREDICTING AGE USING HUMAN FACIAL IMAGES
Keywords:
Age Group Identification, Active Appearace Model (AAM), Wrinkle Analysis, Facial Landmark Points, Mean Classification AlgorithmAbstract
Age estimation plays vital role in human computer interaction where the image is given as input to the
system after which, with the applied techniques the system provides result. An age group prediction system is estimated
through AAM (Active Appearance Model) which calculates the texture and shape. The wrinkle is identified as a part of
the shape information and the features such as eye, nose, chin, lip, cheeks are extracted using PCA(Principle Component
Analysis ) of AAM which then calculates the distance between the features are stored as facial landmark points. The
points are fed as input to the Mean Classification Algorithm which classifies based on two age group adult and
old. Finally the Mean Absolute Error(MAE) value is estimated to determine the accuracy.
