Counting People in Crowds Using Multiple Column Neural Networks

Christian Konishi; Helio Pedrini

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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.

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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