Skip to Main content Skip to Navigation
Conference papers

Can 3D Shape of the Face Reveal your Age?

Baiqiang Xia 1 Boulbaba Ben Amor 1 Mohamed Daoudi 1 Hassen Drira 1 
LIFL - Laboratoire d'Informatique Fondamentale de Lille
Abstract : Age reflects the continuous accumulation of durable effects from the past since birth. Human faces deform with time non-inversely and thus contains their aging information. In addition to its richness with anatomy information, 3D shape of faces could have the advantage of less dependent on pose and independent of illumination, while it hasn't been noticed in literature. Thus, in this work we investigate the age estimation problem from 3D shape of the face. With several descriptions grounding on Riemannian shape analysis of facial curves, we first extracted features from ideas of face Averageness, face Symmetry, its shape variations with Spatial and Gradient descriptors. Then, using the Random Forest-based Regression, experiments are carried out following the Leaving-One-Person-Out (LOPO) protocol on the FRGCv2 dataset. The proposed approach performs with a Mean Absolute Error (MAE) of 3:29 years using a gender-general test protocol. Finally, with the gender-specific experiments, which first separate the 3D scans into Female and Male subsets, then train and test on each gender specific subset in LOPO fashion, we improves the MAE to 3:15 years, which confirms the idea that the aging effect differs with gender.
Document type :
Conference papers
Complete list of metadata

Cited literature [29 references]  Display  Hide  Download
Contributor : Boulbaba Ben Amor Connect in order to contact the contributor
Submitted on : Wednesday, November 13, 2013 - 3:14:14 PM
Last modification on : Friday, November 26, 2021 - 9:58:07 AM
Long-term archiving on: : Friday, February 14, 2014 - 3:46:28 PM


Files produced by the author(s)


  • HAL Id : hal-00904007, version 1


Baiqiang Xia, Boulbaba Ben Amor, Mohamed Daoudi, Hassen Drira. Can 3D Shape of the Face Reveal your Age?. International Conference on Computer Vision Theory and Applications, Jan 2014, Lisbonne, Portugal. ⟨hal-00904007⟩



Record views


Files downloads