Authors:
Marcos Vinicius Mussel Cirne
and
Helio Pedrini
Affiliation:
University of Campinas, Brazil
Keyword(s):
Age Estimation, Image Analysis, Texture, Geometric Descriptor.
Related
Ontology
Subjects/Areas/Topics:
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
Abstract:
Automatic age estimation from facial images has recently received an increasing interest due to a variety
of applications, such as surveillance, human-computer interaction, forensics, and recommendation systems.
Despite such advances, age estimation remains an open problem due to several challenges associated with
the aging process. In this work, we develop and analyze an automatic age estimation method from face
images based on a combination of textural and geometric features. Experiments are conducted on the Adience
dataset (Adience Benchmark, 2017; Eidinger et al., 2014), a large known benchmark used to evaluate both age
and gender classification approaches.