Age Estimation Using Bio-Inspired Features and DCT Coefficients

This paper proposed a novel method which can improve the accuracy of human age estimation greatly. The proposed method was based on "HMAX" model and merges the information of DCT. First, Gabor filters were applied to extract the biological inspiration features. Second, zero mean-variance was applied on the picescs to obtain the responsed results. Finally, DCT transform was applied on the responsed results and the DCT coefficients was the output of the method. There were two reasons for us to propose the method: first, DCT coefficients contained the frequency information; Second, humen were sensitive to the information of different frequencies. To show the effectiveness of the proposed method, we done a lot of experiements on the public FG-NET age database and compared the results with other methods. The results shown that the proposed method can improve the accuracy of human age estimation greatly.