loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Author: Victor Chernyshov

Affiliation: Lomonosov Moscow State Universitty, Russian Federation

Keyword(s): Hand Biometrics, Client-server System, Continuous Skeletons, Hand Detection, Hand Shape, Finger Knuckle Print.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Mobile Imaging

Abstract: In this paper, an efficient method for hand detection based on continuous skeletons approach is presented. It showcased real-time working speed and high detection accuracy (3-5% both FAR and FRR) on a large dataset (50 persons, 80 videos, 2322 frames). This makes the method suitable for use as a part of modern hand biometrics systems including mobile ones. Next, the study shows that continuous skeletons approach can be used as prior for object and background color models in segmentation methods with supervised learning (e.g. interactive segmentation with seeds or abounding box). This fact was successfully adopted to the developed client-server hand recognition system — both thumbnailed colored frame and extracted seeds are sent from Android application to server where Grabcut segmentation is performed. As a result, more qualitative hand shape features are extracted which is confirmed by several identification experiments. Finally, it is demonstrated that hand detection results can be used as a region of interest localization routine in the subsequent analysis of finger knuckle print. The future research will be devoted to extracting features from dorsal fingers surface and developing multi-modal classifier (hand shape and knuckle print features) for identification problem. (More)

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 3.238.195.81

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:
Chernyshov, V. (2015). Efficient Hand Detection on Client-server Recognition System. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 461-468. DOI: 10.5220/0005315704610468

@conference{visapp15,
author={Victor Chernyshov.},
title={Efficient Hand Detection on Client-server Recognition System},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP},
year={2015},
pages={461-468},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005315704610468},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP
TI - Efficient Hand Detection on Client-server Recognition System
SN - 978-989-758-090-1
IS - 2184-4321
AU - Chernyshov, V.
PY - 2015
SP - 461
EP - 468
DO - 10.5220/0005315704610468
PB - SciTePress