loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Enes Dayangac ; Christian Wiede ; Julia Richter and Gangolf Hirtz

Affiliation: Technische Universität Chemnitz, Germany

ISBN: 978-989-758-090-1

Keyword(s): Person Detection, Head-shoulder Detection, Ambient Assisted Living, Latent SVM, DPM, ACF-Detector.

Abstract: Conventional person detection algorithms lack of robustness, especially when the person is partially occluded. We propose thereby a robust head-shoulder detector in 2-D images using deformable part-based models. This detector can be used in a variety of applications such as people counting and person dwell time measurements. In experiments, we compare the head-shoulder detector with the full body detector quantitatively and analyze the robustness of the detector in realistic scenarios. In the results, we show that the model learned with our method outperforms other methods proposed in related work on an ambient assisted living application.

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 100.26.176.182

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:
Dayangac, E.; Wiede, C.; Richter, J. and Hirtz, G. (2015). Robust Head-shoulder Detection using Deformable Part-based Models.In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, pages 236-243. DOI: 10.5220/0005266002360243

@conference{visapp15,
author={Enes Dayangac. and Christian Wiede. and Julia Richter. and Gangolf Hirtz.},
title={Robust Head-shoulder Detection using Deformable Part-based Models},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={236-243},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005266002360243},
isbn={978-989-758-090-1},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - Robust Head-shoulder Detection using Deformable Part-based Models
SN - 978-989-758-090-1
AU - Dayangac, E.
AU - Wiede, C.
AU - Richter, J.
AU - Hirtz, G.
PY - 2015
SP - 236
EP - 243
DO - 10.5220/0005266002360243

Login or register to post comments.

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