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Authors: Diana Borza 1 ; Adrian Darabant 2 and Radu Danescu 1

Affiliations: 1 Technical University of Cluj-Napoca, Romania ; 2 Babes Bolyai University, Romania

Keyword(s): Skin Tone, Color Classification, Support Vector Machine, Convolutional Neural Networks.

Related Ontology Subjects/Areas/Topics: Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis

Abstract: In this paper we propose a skin tone classification system on three skin colors: dark, medium and light. We work on two methods which don’t require any camera or color calibration. The first computes color histograms in various color spaces on representative facial sliding patches that are further combined in a large feature vector. The dimensionality of this vector is reduced using Principal Component Analysis a Support Vector Machine determines the skin color of each region. The skin tone is extrapolated using a voting schema. The second method uses Convolutional Neural Networks to automatically extract chromatic features from augmented sets of facial images. Both algorithms were trained and tested on publicly available datasets. The SVM method achieves an accuracy of 86.67%, while the CNN approach obtains an accuracy of 91.29%. The proposed system is developed as an automatic analysis module in an optical visagism system where the skin tone is used in an eyewear virtual try-on sof tware that allows users to virtually try glasses on their face using a mobile device with a camera. The system proposes only esthetically and functionally fit frames to the user, based on some facial features –skin tone included. (More)

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Paper citation in several formats:
Borza, D.; Darabant, A. and Danescu, R. (2018). Automatic Skin Tone Extraction for Visagism Applications. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP; ISBN 978-989-758-290-5; ISSN 2184-4321, SciTePress, pages 466-473. DOI: 10.5220/0006711104660473

@conference{visapp18,
author={Diana Borza. and Adrian Darabant. and Radu Danescu.},
title={Automatic Skin Tone Extraction for Visagism Applications},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP},
year={2018},
pages={466-473},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006711104660473},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 4: VISAPP
TI - Automatic Skin Tone Extraction for Visagism Applications
SN - 978-989-758-290-5
IS - 2184-4321
AU - Borza, D.
AU - Darabant, A.
AU - Danescu, R.
PY - 2018
SP - 466
EP - 473
DO - 10.5220/0006711104660473
PB - SciTePress

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