Human age estimation using bio-inspired features

• Published in: 2009 IEEE Conference on Computer Vision and Pattern Recognition pp. 112 - 119
• Main Authors: Guodong Guo, Guowang Mu, Yun Fu, Huang, Thomas S
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2009
• Subjects: Aging; Biological information theory; Biological system modeling; Face; Gabor filters; Humans; Image databases; Internet; Prototypes; State estimation
• ISBN: 1424439922; 9781424439928
• ISSN: 1063-6919; 1063-6919
• DOI: 10.1109/CVPR.2009.5206681

We investigate the biologically inspired features (BIF) for human age estimation from faces. As in previous bio-inspired models, a pyramid of Gabor filters are used at all positions of the input image for the S 1 units. But unlike previous models, we find that the pre-learned prototypes for the S 2 layer and then progressing to C 2 cannot work well for age estimation. We also propose to use Gabor filters with smaller sizes and suggest to determine the number of bands and orientations in a problem-specific manner, rather than using a predefined number. More importantly, we propose a new operator "STD" to encode the aging subtlety on faces. Evaluated on the large database YGA with 8,000 face images and the public available FG-NET database, our approach achieves significant improvements in age estimation accuracy over the state-of-the-art methods. By applying our system to some Internet face images, we show the robustness of our method and the potential of cross-race age estimation, which has not been explored by any studies before.