loading
Papers

Research.Publish.Connect.

Paper

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

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

ISBN: 978-989-758-290-5

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 soft ware 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)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.210.22.132

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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 - Volume 4: VISAPP, ISBN 978-989-758-290-5, 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 - Volume 4: VISAPP,},
year={2018},
pages={466-473},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006711104660473},
isbn={978-989-758-290-5},
}

TY - CONF

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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.