@article {14869,
	title = {Face Verification Across Age Progression Using Discriminative Methods},
	journal = {Information Forensics and Security, IEEE Transactions on},
	volume = {5},
	year = {2010},
	month = {2010/03//},
	pages = {82 - 91},
	abstract = {Face verification in the presence of age progression is an important problem that has not been widely addressed. In this paper, we study the problem by designing and evaluating discriminative approaches. These directly tackle verification tasks without explicit age modeling, which is a hard problem by itself. First, we find that the gradient orientation, after discarding magnitude information, provides a simple but effective representation for this problem. This representation is further improved when hierarchical information is used, which results in the use of the gradient orientation pyramid (GOP). When combined with a support vector machine GOP demonstrates excellent performance in all our experiments, in comparison with seven different approaches including two commercial systems. Our experiments are conducted on the FGnet dataset and two large passport datasets, one of them being the largest ever reported for recognition tasks. Second, taking advantage of these datasets, we empirically study how age gaps and related issues (including image quality, spectacles, and facial hair) affect recognition algorithms. We found surprisingly that the added difficulty of verification produced by age gaps becomes saturated after the gap is larger than four years, for gaps of up to ten years. In addition, we find that image quality and eyewear present more of a challenge than facial hair.},
	keywords = {algorithms;support, databases;, dataset;age, FGnet, hair;gradient, information;image, information;recognition, machine;face, machines;visual, methods;eyewear;face, methods;support, orientation, orientation;gradient, progression;commercial, pyramid;hierarchical, quality;magnitude, recognition;gradient, systems;discriminative, vector, verification;facial},
	isbn = {1556-6013},
	doi = {10.1109/TIFS.2009.2038751},
	author = {Ling,Haibin and Soatto,S. and Ramanathan,N. and Jacobs, David W.}
}
@conference {14862,
	title = {A Study of Face Recognition as People Age},
	booktitle = {Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on},
	year = {2007},
	month = {2007/10//},
	pages = {1 - 8},
	abstract = {In this paper we study face recognition across ages within a real passport photo verification task. First, we propose using the gradient orientation pyramid for this task. Discarding the gradient magnitude and utilizing hierarchical techniques, we found that the new descriptor yields a robust and discriminative representation. With the proposed descriptor, we model face verification as a two-class problem and use a support vector machine as a classifier. The approach is applied to two passport data sets containing more than 1,800 image pairs from each person with large age differences. Although simple, our approach outperforms previously tested Bayesian technique and other descriptors, including the intensity difference and gradient with magnitude. In addition, it works as well as two commercial systems. Second, for the first time, we empirically study how age differences affect recognition performance. Our experiments show that, although the aging process adds difficulty to the recognition task, it does not surpass illumination or expression as a confounding factor.},
	keywords = {Bayesian, difference;passport, machine;face, machines;, magnitude;gradient, orientation, photo, pyramid;hierarchical, recognition;face, recognition;support, representation;face, task;support, technique;discriminative, techniques;intensity, vector, verification, verification;gradient},
	doi = {10.1109/ICCV.2007.4409069},
	author = {Ling,Haibin and Soatto,S. and Ramanathan,N. and Jacobs, David W.}
}
