research-article

A smile can reveal your age: enabling facial dynamics in age estimation

Authors:

Hamdi Dibeklioğlu,

Albert Ali Salah,

Roberto ValentiAuthors Info & Claims

MM '12: Proceedings of the 20th ACM international conference on Multimedia

Pages 209 - 218

https://doi.org/10.1145/2393347.2393382

Published: 29 October 2012 Publication History

Abstract

Estimation of a person's age from the facial image has many applications, ranging from biometrics and access control to cosmetics and entertainment. Many image-based methods have been proposed for this problem. In this paper, we propose a method for the use of dynamic features in age estimation, and show that 1) the temporal dynamics of facial features can be used to improve image-based age estimation; 2) considered alone, static image-based features are more accurate than dynamic features. We have collected and annotated an extensive database of face videos from 400 subjects with an age range between 8 and 76, which allows us to extensively analyze the relevant aspects of the problem. The proposed system, which fuses facial appearance and expression dynamics, performs with a mean absolute error of 4.81 (4.87) years. This represents a significant improvement of accuracy in comparison to the sole use of appearance-based features.

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Cited By

Kurosumi MYabuzaki JKuribayashi MMizukoshi K(2024)Age‐related changes in cheek skin movement: A case study of Japanese womenSkin Research and Technology10.1111/srt.1376830:7Online publication date: 3-Jul-2024
https://doi.org/10.1111/srt.13768
Yokoyama EFrancois GHarrar MBachatene CUdodaira KTrévisan SNicolas AVelleman DFlament F(2023)Video‐based paired comparison to evaluate some cosmetic products under camera movement for dynamic performanceInternational Journal of Cosmetic Science10.1111/ics.1285745:4(480-487)Online publication date: 27-Apr-2023
https://doi.org/10.1111/ics.12857
Nagaraju KReddy M(2022)An Ensemble Auto-Encoder for Age Estimation Based on Human Facial Expressions2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)10.1109/ICSES55317.2022.9914215(1-6)Online publication date: 15-Jul-2022
https://doi.org/10.1109/ICSES55317.2022.9914215
Show More Cited By

Index Terms

A smile can reveal your age: enabling facial dynamics in age estimation
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Video summarization
    2. Philosophical/theoretical foundations of artificial intelligence
      1. Cognitive science
2. Human-centered computing
  1. Human computer interaction (HCI)

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Information

Published In

cover image ACM Conferences

MM '12: Proceedings of the 20th ACM international conference on Multimedia

October 2012

1584 pages

ISBN:9781450310895

DOI:10.1145/2393347

General Chairs:
Noboru Babaguchi
Osaka University, Japan
,
Kiyoharu Aizawa
The University of Tokyo, Japan
,
John Smith
IBM, USA
,
Program Chairs:
Shin'ichi Satoh
National Institute of Informatics, Japan
,
Thomas Plagemann
University of Oslo, Norway
,
Xian-Sheng Hua
Microsoft, USA
,
Rong Yan
Facebook, USA

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 October 2012

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MM '12

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SIGMM

MM '12: ACM Multimedia Conference

October 29 - November 2, 2012

Nara, Japan

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

Kurosumi MYabuzaki JKuribayashi MMizukoshi K(2024)Age‐related changes in cheek skin movement: A case study of Japanese womenSkin Research and Technology10.1111/srt.1376830:7Online publication date: 3-Jul-2024
https://doi.org/10.1111/srt.13768
Yokoyama EFrancois GHarrar MBachatene CUdodaira KTrévisan SNicolas AVelleman DFlament F(2023)Video‐based paired comparison to evaluate some cosmetic products under camera movement for dynamic performanceInternational Journal of Cosmetic Science10.1111/ics.1285745:4(480-487)Online publication date: 27-Apr-2023
https://doi.org/10.1111/ics.12857
Nagaraju KReddy M(2022)An Ensemble Auto-Encoder for Age Estimation Based on Human Facial Expressions2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)10.1109/ICSES55317.2022.9914215(1-6)Online publication date: 15-Jul-2022
https://doi.org/10.1109/ICSES55317.2022.9914215
Becerra-Riera FMorales-González AMéndez-Vázquez HDugelay J(2022)Demographic attribute estimation in face videos combining local information and quality assessmentMachine Vision and Applications10.1007/s00138-021-01269-433:2Online publication date: 3-Feb-2022
https://doi.org/10.1007/s00138-021-01269-4
Becerra-Riera FMorales-Gonzalez AMendez-Vazquez HDugelay J(2021)Attribute-based quality assessment for demographic estimation in face videos2020 25th International Conference on Pattern Recognition (ICPR)10.1109/ICPR48806.2021.9412164(5875-5882)Online publication date: 10-Jan-2021
https://doi.org/10.1109/ICPR48806.2021.9412164
Turzo NRabiul Islam M(2021)AdaBoost Classifier-Based Binary Age Group Stratification by CASIA Iris ImageProceedings of International Joint Conference on Advances in Computational Intelligence10.1007/978-981-16-0586-4_42(525-537)Online publication date: 18-May-2021
https://doi.org/10.1007/978-981-16-0586-4_42
Tufekcioglu ZBilgic BZeylan ASalah ADibeklioglu HEmre M(2020)Do Alzheimer’s Disease Patients Appear Younger than Their Real Age?Dementia and Geriatric Cognitive Disorders10.1159/00051035949:5(483-488)Online publication date: 20-Oct-2020
https://doi.org/10.1159/000510359
Pei WDibeklioglu HBaltrusaitis TTax D(2020)Attended End-to-End Architecture for Age Estimation From Facial Expression VideosIEEE Transactions on Image Processing10.1109/TIP.2019.294828829(1972-1984)Online publication date: 2020
https://doi.org/10.1109/TIP.2019.2948288
Kim MLee HLee SRo Y(2020)Robust Video Facial Authentication With Unsupervised Mode Disentanglement2020 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP40778.2020.9191052(1321-1325)Online publication date: Oct-2020
https://doi.org/10.1109/ICIP40778.2020.9191052
Kröger JLutz OMüller F(2020)What Does Your Gaze Reveal About You? On the Privacy Implications of Eye TrackingPrivacy and Identity Management. Data for Better Living: AI and Privacy10.1007/978-3-030-42504-3_15(226-241)Online publication date: 6-Mar-2020
https://doi.org/10.1007/978-3-030-42504-3_15
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