Age estimation under changes in image quality: An experimental study
In this paper, we investigate the influence of image quality on the performance of aging features. Age estimation systems used or designed a number of aging features to capture the aging cues from the face such as skin texture and wrinkles. These aging cues are sensitive to small changes in the imaging conditions which suggests considering the imaging quality when extracting such information. Although interesting performances are reported on various datasets, the effect of image quality has not been addressed. We introduce a scheme to explore the influence of image quality on the performance of appearance aging features. A number of datasets are experimented on where artifacts resulted from different types of noise are considered. Finally, we propose a method to automatically apply the most suitable features based on the quality of the image. The results show that better or comparable performance is obtained when automatically applying different features, based on image quality, in comparison to a single (best) feature type.