loading
Papers

Research.Publish.Connect.

Paper

Authors: Zhixin Guo ; Wenzhi Liao ; Peter Veelaert and Wilfried Philips

Affiliation: Ghent University-IMEC, Belgium

ISBN: 978-989-758-276-9

Keyword(s): Pedestrian Detection, Occlusion Handling, Adaboost, Integral Channel Features.

Related Ontology Subjects/Areas/Topics: Feature Selection and Extraction ; Pattern Recognition ; Theory and Methods

Abstract: Pedestrian detection has achieved a remarkable progress in recent years, but challenges remain especially when occlusion happens. Intuitively, occluded pedestrian samples contain some characteristic occlusion appearance features that can help to improve detection. However, we have observed that most existing approaches intentionally avoid using samples of occluded pedestrians during the training stage. This is because such samples will introduce unreliable information, which affects the learning of model parameters and thus results in dramatic performance decline. In this paper, we propose a new framework for pedestrian detection. The proposed method exploits the use of occluded pedestrian samples to learn more robust features for discriminating pedestrians, and enables better performances on pedestrian detection, especially for the occluded pedestrians (which always happens in many real applications). Compared to some recent detectors on Caltech Pedestrian dataset, with our proposed method, detection miss rate for occluded pedestrians are significantly reduced. (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 35.172.217.40

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:
Guo, Z.; Liao, W.; Veelaert, P. and Philips, W. (2018). Occlusion-robust Detector Trained with Occluded Pedestrians.In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, pages 86-94. DOI: 10.5220/0006569200860094

@conference{icpram18,
author={Zhixin Guo. and Wenzhi Liao. and Peter Veelaert. and Wilfried Philips.},
title={Occlusion-robust Detector Trained with Occluded Pedestrians},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={86-94},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006569200860094},
isbn={978-989-758-276-9},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Occlusion-robust Detector Trained with Occluded Pedestrians
SN - 978-989-758-276-9
AU - Guo, Z.
AU - Liao, W.
AU - Veelaert, P.
AU - Philips, W.
PY - 2018
SP - 86
EP - 94
DO - 10.5220/0006569200860094

Login or register to post comments.

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