loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Chao Sun and Won-Sook Lee

Affiliation: University of Ottawa, Canada

Keyword(s): Braid Hairstyle Recognition, Convolutional Neural Networks.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping

Abstract: In this paper, we present a novel braid hairstyle recognition system based on Convolutional Neural Networks (CNNs). We first build a hairstyle patch dataset that is composed of braid hairstyle patches and non-braid hairstyle patches (straight hairstyle patches, curly hairstyle patches, and kinky hairstyle patches). Then we train our hairstyle recognition system via transfer learning on a pre-trained CNN model in order to extract the features of different hairstyles. Our hairstyle recognition CNN model achieves the accuracy of 92.7% on image patch dataset. Then the CNN model is used to perform braid hairstyle detection and recognition in full-hair images. The experiment results shows that the patch-level trained CNN model can successfully detect and recognize braid hairstyle in image-level.

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 3.145.110.99

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:
Sun, C. and Lee, W. (2017). Braid Hairstyle Recognition based on CNNs. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP; ISBN 978-989-758-225-7; ISSN 2184-4321, SciTePress, pages 548-555. DOI: 10.5220/0006169805480555

@conference{visapp17,
author={Chao Sun. and Won{-}Sook Lee.},
title={Braid Hairstyle Recognition based on CNNs},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP},
year={2017},
pages={548-555},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006169805480555},
isbn={978-989-758-225-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP
TI - Braid Hairstyle Recognition based on CNNs
SN - 978-989-758-225-7
IS - 2184-4321
AU - Sun, C.
AU - Lee, W.
PY - 2017
SP - 548
EP - 555
DO - 10.5220/0006169805480555
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic