TY - GEN
T1 - Human age estimation using bio-inspired features
AU - Guo, Guodong
AU - Mu, Guowang
AU - Fu, Yun
AU - Huang, Thomas S.
PY - 2009
Y1 - 2009
N2 - We investigate the biologically inspired features (BIF) for human age estimation from faces. As in previous bioinspired models, a pyramid of Gabor filters are used at all positions of the input image for the S1 units. But unlike previous models, we find that the pre-learned prototypes for the S2 layer and then progressing to C2 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-artmethods. 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
AB - We investigate the biologically inspired features (BIF) for human age estimation from faces. As in previous bioinspired models, a pyramid of Gabor filters are used at all positions of the input image for the S1 units. But unlike previous models, we find that the pre-learned prototypes for the S2 layer and then progressing to C2 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-artmethods. 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
UR - http://www.scopus.com/inward/record.url?scp=70450194783&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70450194783&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2009.5206681
DO - 10.1109/CVPRW.2009.5206681
M3 - Conference contribution
AN - SCOPUS:70450194783
SN - 9781424439935
T3 - 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009
SP - 112
EP - 119
BT - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
PB - IEEE Computer Society
T2 - 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009
Y2 - 20 June 2009 through 25 June 2009
ER -