Facial Makeup Detection using the CMYK Color Model and Convolutional Neural Networks

Bertacchi M.G.; Silveira I.F.

Facial Makeup Detection using the CMYK Color Model and Convolutional Neural Networks

Tipo

Artigo de evento

Data de publicação

2019

Periódico

Proceedings - 15th Workshop of Computer Vision, WVC 2019

Citações (Scopus)

2

Autores

Bertacchi M.G.
Silveira I.F.

Resumo

© 2019 IEEE.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.

Assuntos Scopus

CMYK , Color modeling , Convolutional neural network , Detection process , Environment conditions , HSV color models , Image database , Regions of interest