DocumentCode :
3185353
Title :
Recent advances in age and height estimation from still images and video
Author :
Chellappa, Rama ; Turaga, Pavan
Author_Institution :
Center for Autom. Res., Univ. of Maryland, College Park, MD, USA
fYear :
2011
fDate :
21-25 March 2011
Firstpage :
91
Lastpage :
96
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 :
biometrics (access control); geometry; image fusion; statistical analysis; video signal processing; age estimation; height estimation; image-formation model fusion; multiview-geometry; shape-space geometry; soft-biometrics; statistical methods; Calibration; Estimation; Geometry; Humans; Legged locomotion; Robustness; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
978-1-4244-9140-7
Type :
conf
DOI :
10.1109/FG.2011.5771367
Filename :
5771367
Link To Document :
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