Piecewise linear aging function for facial age estimation

Instead of constructing a complex aging model on the whole age space, a piecewise linear aging function is proposed to approximate the ground truth aging function locally. To handle the `regression toward the mean´ problem of local aging function regression, a weighting strategy is used to assign larger weights to the samples near typical aging appearance of each age. In age estimation step, a global aging function is used to predict the test sample´s rough age range and the local linear aging function on that range is then used to give a final result. Experimental results show that our method can get more accuracy results in facial age estimation.