@conference {12453,
	title = {Recent advances in age and height estimation from still images and video},
	booktitle = {2011 IEEE International Conference on Automatic Face \& Gesture Recognition and Workshops (FG 2011)},
	year = {2011},
	month = {2011/03/21/25},
	pages = {91 - 96},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Soft-biometrics such as gender, age, race, etc have been found to be useful characterizations that enable fast pre-filtering and organization of data for biometric applications. In this paper, we focus on two useful soft-biometrics - age and height. We discuss their utility and the factors involved in their estimation from images and videos. In this context, we highlight the role that geometric constraints such as multiview-geometry, and shape-space geometry play. Then, we present methods based on these geometric constraints for age and height-estimation. These methods provide a principled means by fusing image-formation models, multi-view geometric constraints, and robust statistical methods for inference.},
	keywords = {age estimation, biometrics (access control), Calibration, Estimation, Geometry, height estimation, HUMANS, image fusion, image-formation model fusion, Legged locomotion, multiview-geometry, Robustness, SHAPE, shape-space geometry, soft-biometrics, statistical analysis, statistical methods, video signal processing},
	isbn = {978-1-4244-9140-7},
	doi = {10.1109/FG.2011.5771367},
	author = {Chellapa, Rama and Turaga,P.}
}
