Recent advances in age and height estimation from still images and video

Rama Chellappa, Pavan Turaga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
Pages91-96
Number of pages6
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 - Santa Barbara, CA, United States
Duration: Mar 21 2011Mar 25 2011

Other

Other2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
CountryUnited States
CitySanta Barbara, CA
Period3/21/113/25/11

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

Cite this

Chellappa, R., & Turaga, P. (2011). Recent advances in age and height estimation from still images and video. In 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 (pp. 91-96). [5771367] https://doi.org/10.1109/FG.2011.5771367