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Authors: Mohamed Selim 1 ; Shekhar Raheja 2 and Didier Stricker 3

Affiliations: 1 German Research Center for Artificial Intelligence and DFKI, Germany ; 2 Technical University Kaiserslautern, Germany ; 3 DFKI, German Research Center for Artificial Intelligence and DFKI, Germany

ISBN: 978-989-758-090-1

Keyword(s): Age-group Estimation, Local Binary Patterns, Extended Local Binary Patterns, Real-time, K-Nearest Neighbours.

Related Ontology Subjects/Areas/Topics: Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

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 s peeding up the entire process as the feature vector’s length has been reduced significantly, which optimises the process for real-time applications. (More)

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Paper citation in several formats:
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 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, pages 408-415. DOI: 10.5220/0005311604080415

@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 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={408-415},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005311604080415},
isbn={978-989-758-090-1},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: 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

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