Face age estimation by using Bisection Search Tree

Age estimation via face images has recently attracted a lot of researches in computer vision, due to its many potential applications. In this paper, a novel Bisection Search Tree (BST) algorithm is proposed for face age estimation, based on the idea of Divide and Conquer. Different from those conventional classification or regression approaches, the BST first constructs a binary tree according to the whole age range of training set, and then learns decision functions for all non-leaf nodes to determine which child node a test sample will be passed to. Gabor wavelet face representation and dimensionality reduction by using Linear Discriminative Analysis are also adopted in this paper. Experimental results on two public aging databases, MORPH-II and MEDS-II, show that the BST method is effective for age estimation and outperforms other state-of-the-art approaches.