A comparative study of human facial age ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
A comparative study of human facial age estimation: handcrafted features vs. deep features
Auteur(s) :
Bekhouche, S. E. [Auteur]
University of the Basque Country = Euskal Herriko Unibertsitatea [UPV / EHU]
Dornaika, F. [Auteur correspondant]
Benlamoudi, A. [Auteur]
Ouafi, A. [Auteur]
Laboratoire Energie Signal Images et Automatique [Univ Ngaoundéré] [LESIA]
Tahleb Ahmed, Abdelmalik [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - Département Opto-Acousto-Électronique - UMR 8520 [IEMN-DOAE]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
University of the Basque Country = Euskal Herriko Unibertsitatea [UPV / EHU]
Dornaika, F. [Auteur correspondant]
Benlamoudi, A. [Auteur]
Ouafi, A. [Auteur]
Laboratoire Energie Signal Images et Automatique [Univ Ngaoundéré] [LESIA]
Tahleb Ahmed, Abdelmalik [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - Département Opto-Acousto-Électronique - UMR 8520 [IEMN-DOAE]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Titre de la revue :
Multimedia Tools and Applications
Pagination :
26605-26622
Éditeur :
Springer Verlag
Date de publication :
2020-09
ISSN :
1380-7501
Mot(s)-clé(s) en anglais :
Age estimation
Handcrafted features
Deep features
Support vector regression
Handcrafted features
Deep features
Support vector regression
Discipline(s) HAL :
Sciences de l'ingénieur [physics]
Informatique [cs]
Informatique [cs]/Réseaux et télécommunications [cs.NI]
Informatique [cs]/Intelligence artificielle [cs.AI]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Sciences de l'ingénieur [physics]/Electronique
Informatique [cs]
Informatique [cs]/Réseaux et télécommunications [cs.NI]
Informatique [cs]/Intelligence artificielle [cs.AI]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Sciences de l'ingénieur [physics]/Electronique
Résumé en anglais : [en]
In recent times, the topic of human facial age estimation attracted much attention. This is due to its ability to improve biometrics systems. Recently, several applications that are based on the demographic attributes ...
Lire la suite >In recent times, the topic of human facial age estimation attracted much attention. This is due to its ability to improve biometrics systems. Recently, several applications that are based on the demographic attributes estimation have been developed. These include law enforcement, re-identification in videos, planed marketing, intelligent advertising, social media, and human-computer interaction. The main contributions of the paper are as follows. Firstly, it extends some handcrafted models that are based on the Pyramid Multi Level (PML) face representation. Secondly, it evaluates the performance of two different kinds of features that are handcrafted and deep features. It compares handcrafted and deep features in terms of accuracy and computational complexity. The proposed scheme of study includes the following three main steps: 1) face preprocessing; 2) feature extraction (two different kinds of features are studied: handcrafted and deep features); 3) feeding the obtained features to a linear regressor. In addition, we investigate the strengths and weaknesses of handcrafted and deep features when used in facial age estimation. Experiments are run on three public databases (FG-NET, PAL and FACES). These experiments show that both handcrafted and deep features are effective for facial age estimation.Lire moins >
Lire la suite >In recent times, the topic of human facial age estimation attracted much attention. This is due to its ability to improve biometrics systems. Recently, several applications that are based on the demographic attributes estimation have been developed. These include law enforcement, re-identification in videos, planed marketing, intelligent advertising, social media, and human-computer interaction. The main contributions of the paper are as follows. Firstly, it extends some handcrafted models that are based on the Pyramid Multi Level (PML) face representation. Secondly, it evaluates the performance of two different kinds of features that are handcrafted and deep features. It compares handcrafted and deep features in terms of accuracy and computational complexity. The proposed scheme of study includes the following three main steps: 1) face preprocessing; 2) feature extraction (two different kinds of features are studied: handcrafted and deep features); 3) feeding the obtained features to a linear regressor. In addition, we investigate the strengths and weaknesses of handcrafted and deep features when used in facial age estimation. Experiments are run on three public databases (FG-NET, PAL and FACES). These experiments show that both handcrafted and deep features are effective for facial age estimation.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Source :