Image Based Human Age Estimation Using Principle Component Analysis/ Artificial Neural Network

Estimating age of a person from captured image of His/ Her face is a difficult task. In general the exciting technique to this problem is feature vector. Human Computer Interaction (HCI) for designing automatic age estimation systems via facial dynamics. The success of such research may bring in many innovative HCI tools used for the applications of human-centered multimedia communication. The aging patterns can be effectively extracted from a discriminate subspace-learning algorithm and visualize as distinct manifold structures. The existing method used is Principal component analysis. Artificial neural network is intuitive to apply manifold analysis to age estimation to bring out the advantage of manifold learning, such methods should combined with the appropriate regression models for a new testing image, fit extract low dimensional feature with the learned regression model to estimate the exact age or an age interval.