Real-time Human Age Estimation based on Facial Images using Uniform Local Binary Patterns

Mohamed Selim, Shekhar Raheja, Didier Stricker

2015

Abstract

This paper summarizes work done on real-time human age-group estimation based on frontal facial images. Our approach relies on detecting visible ageing effects, such as facial skin texture. This information is described using uniform Local Binary Patterns (LBP) and the estimation is done using the K-Nearest Neighbour classifier. In the current work, the system is trained using the FERET dataset. The training data is divided into five main age groups. Facial images captured in real-time using the Microsoft Kinect RGB data are used to classify the subjects age into one of the five different age groups. An accuracy of 81% was achieved on the live testing data. In the proposed approach, only facial regions affected by the ageing process are used in the face description. Moreover, the use of uniform Local Binary Patterns is evaluated in the context of facial description and age-group estimation. Results show that the uniform LBP depicts most of the facial texture information. That led to speeding up the entire process as the feature vector’s length has been reduced significantly, which optimises the process for real-time applications.

Paper Citation

in Harvard Style

Selim M., Raheja S. and Stricker D. (2015). Real-time Human Age Estimation based on Facial Images using Uniform Local Binary Patterns . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, pages 408-415. DOI: 10.5220/0005311604080415

in Bibtex Style

@conference{visapp15,
author={Mohamed Selim and Shekhar Raheja and Didier Stricker},
title={Real-time Human Age Estimation based on Facial Images using Uniform Local Binary Patterns},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={408-415},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005311604080415},
isbn={978-989-758-090-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)
TI - Real-time Human Age Estimation based on Facial Images using Uniform Local Binary Patterns
SN - 978-989-758-090-1
AU - Selim M.
AU - Raheja S.
AU - Stricker D.
PY - 2015
SP - 408
EP - 415
DO - 10.5220/0005311604080415