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Real-Time Facial Analysis in Still Images and Videos for Gender and Age Estimation

  • Lionel Prevost
  • Philippe Phothisane
  • Erwan Bigorgne
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9443)

Abstract

Research has recently focused on human age and gender estimation because they are useful cues in many applications such as human-machine interaction, soft biometrics and demographic studies.

In this paper, we propose a real time face tracking framework that includes a sequential estimation of people’s gender then age. Local binary patterns histograms extracted from facial images. A single gender estimator and several gender-specific age estimators are trained using a boosting scheme. Their decisions are combined to output a gender and an age in years.

The whole process is thoroughly tested on state-of art databases and video sets. Results on the popular FG-NET database are comparable to human perception (overall 70 % correct responses within 5 years tolerance and almost 90 % within 10 years tolerance). The age and gender estimators combined with the face tracker provide real-time estimations at 21 frames per second.

Keywords

Face analysis LBP Boosting Gender estimation Age estimation 

Notes

Acknowledgements

We provide our test videos including the ground truth measures on request. Please contact us by mail to receive our data. The authors gratefully acknowledge the contribution of the Agence National de la Recherche (CIFRE N°533/2009).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lionel Prevost
    • 1
  • Philippe Phothisane
    • 2
  • Erwan Bigorgne
    • 2
  1. 1.University of the French West IndiesPointe à PitreGuadeloupe
  2. 2.EikeoParisFrance

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