Paper Info
Title
A comparative study of human facial age estimation: handcrafted features vs. deep features
Abstract
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.
Year
DOI
Venue
2020
10.1007/s11042-020-09278-7
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Age estimation,Handcrafted features,Deep features,Support vector regression
Journal
79.0
Issue
ISSN
Citations 
35-36
1380-7501
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
salah eddine bekhouche1323.64
Fadi Dornaika280996.43
azeddine benlamoudi3202.02
abdelkrim ouafi4414.88
Abdelmalik Taleb-ahmed59622.55