Counting People in Crowds Using Multiple Column Neural Networks

Christian Konishi; Helio Pedrini

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Counting People in Crowds Using Multiple Column Neural Networks

Topics: Camera Networks and Vision; Deep Learning for Tracking; Deep Learning for Visual Understanding ; Segmentation and Grouping; Video Surveillance and Event Detection

In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, 363-370, 2023 , Lisbon, Portugal

Authors: Christian Konishi and Helio Pedrini

Affiliation: Institute of Computing, University of Campinas, Campinas, Brazil

Keyword(s): Crowd Counting, Generative Adversarial Networks, Deep Learning, Activation Maps.

Abstract: Crowd counting through images is a research field of great interest for its various applications, such as surveil-lance camera images monitoring, urban planning. In this work, a model (MCNN-U) based on Generative Adversarial Networks (GANs) with Wasserstein cost and Multiple Column Neural Networks (MCNNs) is proposed to obtain better estimates of the number of people. The model was evaluated using two crowd counting databases, UCF-CC-50 and ShanghaiTech. In the first database, the reduction in the mean absolute error was greater than 30%, whereas the gains in efficiency were smaller in the second database. An adaptation of the LayerCAM method was also proposed for the crowd counter network visualization.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 3.14.73.229

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:

Konishi, C. and Pedrini, H. (2023). Counting People in Crowds Using Multiple Column Neural Networks. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 363-370. DOI: 10.5220/0011704000003417

@conference{visapp23,
author={Christian Konishi. and Helio Pedrini.},
title={Counting People in Crowds Using Multiple Column Neural Networks},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={363-370},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011704000003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP
TI - Counting People in Crowds Using Multiple Column Neural Networks
SN - 978-989-758-634-7
IS - 2184-4321
AU - Konishi, C.
AU - Pedrini, H.
PY - 2023
SP - 363
EP - 370
DO - 10.5220/0011704000003417
PB - SciTePress