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Authors: João Carvalho 1 ; Manuel Marques 1 ; João Paulo Costeira 1 and Pedro Mendes Jorge 2

Affiliations: 1 Institute for Systems and Robotics (ISR/IST), LARSyS, Instituto Superior Técnico and Univ. Lisboa, Portugal ; 2 ISEL - Instituto Politécnico de Lisboa, Portugal

Keyword(s): 3D Point Cloud, Depth Camera, Multiple Cameras, Human Detection, Human Classification.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Camera Networks and Vision ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Segmentation and Grouping ; Shape Representation and Matching

Abstract: Real time monitoring of large infrastructures has human detection as a core task. Since the people anonymity is a hard constraint in these scenarios, video cameras can not be used. This paper presents a low cost solution for real time people detection in large crowded environments using multiple depth cameras. In order to detect people, binary classifiers (person/notperson) were proposed based on different sets of features. It is shown that good classification performance can be achieved choosing a small set of simple feature.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Carvalho, J.; Marques, M.; Costeira, J. and Jorge, P. (2016). Detecting People in Large Crowded Spaces using 3D Data from Multiple Cameras. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 218-225. DOI: 10.5220/0005727702180225

@conference{visapp16,
author={João Carvalho. and Manuel Marques. and João Paulo Costeira. and Pedro Mendes Jorge.},
title={Detecting People in Large Crowded Spaces using 3D Data from Multiple Cameras},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP},
year={2016},
pages={218-225},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005727702180225},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP
TI - Detecting People in Large Crowded Spaces using 3D Data from Multiple Cameras
SN - 978-989-758-175-5
IS - 2184-4321
AU - Carvalho, J.
AU - Marques, M.
AU - Costeira, J.
AU - Jorge, P.
PY - 2016
SP - 218
EP - 225
DO - 10.5220/0005727702180225
PB - SciTePress