research-article

Facial-based Intrusion Detection System with Deep Learning in Embedded Devices

Authors:

Giuseppe Amato,

Fabrizio Falchi,

Claudio Gennaro,

Claudio VairoAuthors Info & Claims

SSIP '18: Proceedings of the 2018 International Conference on Sensors, Signal and Image Processing

Pages 64 - 68

https://doi.org/10.1145/3290589.3290598

Published: 12 October 2018 Publication History

Abstract

With the advent of deep learning based methods, facial recognition algorithms have become more effective and efficient. However, these algorithms have usually the disadvantage of requiring the use of dedicated hardware devices, such as graphical processing units (GPUs), which pose restrictions on their usage on embedded devices with limited computational power.

In this paper, we present an approach that allows building an intrusion detection system, based on face recognition, running on embedded devices. It relies on deep learning techniques and does not exploit the GPUs. Face recognition is performed using a knn classifier on features extracted from a 50-layers Residual Network (ResNet-50) trained on the VGGFace2 dataset. In our experiment, we determined the optimal confidence threshold that allows distinguishing legitimate users from intruders.

In order to validate the proposed system, we created a ground truth composed of 15,393 images of faces and 44 identities, captured by two smart cameras placed in two different offices, in a test period of six months. We show that the obtained results are good both from the efficiency and effectiveness perspective.

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Cited By

Bhuckory BPudaruth S(2023)A Multimodal IoT-Based Home Intrusion Detection SystemInternational Journal of Computer Theory and Engineering10.7763/IJCTE.2023.V15.134015:3(117-124)Online publication date: 2023
https://doi.org/10.7763/IJCTE.2023.V15.1340
Edinger JHeck MLummer LWachner ABecker C(2023)Hands-free Mobile Device Control Through Head Pose Estimation2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops56833.2023.10150384(367-373)Online publication date: 13-Mar-2023
https://doi.org/10.1109/PerComWorkshops56833.2023.10150384
Kadhim THariri WSmaoui Zghal NBen Aissa D(2023)A face recognition application for Alzheimer’s patients using ESP32-CAM and Raspberry PiJournal of Real-Time Image Processing10.1007/s11554-023-01357-w20:5Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1007/s11554-023-01357-w
Show More Cited By

Index Terms

Facial-based Intrusion Detection System with Deep Learning in Embedded Devices

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SSIP '18: Proceedings of the 2018 International Conference on Sensors, Signal and Image Processing

October 2018

88 pages

ISBN:9781450366205

DOI:10.1145/3290589

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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CTU: Czech Technical University in Prague

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 October 2018

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SSIP 2018

SSIP 2018: 2018 International Conference on Sensors, Signal and Image Processing

October 12 - 14, 2018

Prague, Czech Republic

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Cited By

Bhuckory BPudaruth S(2023)A Multimodal IoT-Based Home Intrusion Detection SystemInternational Journal of Computer Theory and Engineering10.7763/IJCTE.2023.V15.134015:3(117-124)Online publication date: 2023
https://doi.org/10.7763/IJCTE.2023.V15.1340
Edinger JHeck MLummer LWachner ABecker C(2023)Hands-free Mobile Device Control Through Head Pose Estimation2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops56833.2023.10150384(367-373)Online publication date: 13-Mar-2023
https://doi.org/10.1109/PerComWorkshops56833.2023.10150384
Kadhim THariri WSmaoui Zghal NBen Aissa D(2023)A face recognition application for Alzheimer’s patients using ESP32-CAM and Raspberry PiJournal of Real-Time Image Processing10.1007/s11554-023-01357-w20:5Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1007/s11554-023-01357-w
Amato GFalchi FGennaro CMassoli FPassalis NTefas ATrivilini AVairo C(2019)Face Verification and Recognition for Digital Forensics and Information Security2019 7th International Symposium on Digital Forensics and Security (ISDFS)10.1109/ISDFS.2019.8757511(1-6)Online publication date: Jun-2019
https://doi.org/10.1109/ISDFS.2019.8757511

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