Title
Facial Makeup Detection using the CMYK Color Model and Convolutional Neural Networks
Date Issued
01 September 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
Mackenzie Presbyterian University
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
This work presents a facial makeup detection technique using CMYK and Neural Networks. The main goal is to detect facial makeup using the CMYK color model, and analyzing its results by comparing it to the HSV color model, which is widely used in the literature. In the detection process, each image was separated into regions of interest (the eyes and the whole face). Five image databases were chosen, all varying in lighting and environment conditions. In HSV, 91% of accuracy was achieved on the eye region and 92% on the face. In CMYK, the results obtained had 97% of accuracy on the eye region and 95% on the face. Therefore, based on the results achieved, the CMYK color model, even though it is mainly used in Printing, deserves attention in the area of Computer Vision, involving Makeup Detection.
Start page
54
End page
60
Language
English
OCDE Knowledge area
Ingeniería de sistemas y comunicaciones Ciencias de la computación
Scopus EID
2-s2.0-85074885921
ISBN of the container
9781728153377
Conference
Proceedings - 15th Workshop of Computer Vision, WVC 2019
Sources of information: Directorio de Producción Científica Scopus