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Deep Learning-Based 3D Face Recognition Using Derived Features from Point Cloud

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Innovations in Smart Cities Applications Volume 4 (SCA 2020)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 183))

Abstract

With developing technology and urbanization, smart city applications have increased. Accordingly, this development brought some difficulties such as public security risk. Identifying people’s identities is a requirement in both smart city challenges and smart environment or smart interaction difficulties. Face recognition has a huge potential for people’s identification. It was possible to perform face recognition applications in larger databases and different situations with the development of deep learning methods. 2D images are usually used for face recognition applications. However, different challenges such as pose change and illumination cause difficulties in 2D facial recognition applications. Laser scanning technology has provided the production of 3D point clouds, including the geometric information of the faces. When the point clouds are combined with deep learning techniques, 3D face recognition has great potential. In the study, 2D images were created for facial recognition using feature maps obtained from 3D point clouds. ResNet-18, ResNet-50 and ResNet-101 architectures, which are different versions of ResNet architecture, were used for classification purposes. Bosphorus database was used in the study. 3D Face recognition was performed with different facial expressions and occlusions based on the data of 105 people. As a result of the study, overall accuracy was obtained with ResNet-18, ResNet-50, and ResNet-101 architectures at 77.36%, 77.03% and 81.54% respectively.

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Authors and Affiliations

  1. Department of Geomatics Engineering, Istanbul Technical University, 34469, Maslak, Turkey

    Muhammed Enes Atik & Zaide Duran

Authors
  1. Muhammed Enes Atik
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  2. Zaide Duran
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Correspondence to Muhammed Enes Atik .

Editor information

Editors and Affiliations

  1. Computer Engineering Department, Faculty of Sciences and Techniques, Tangier, Morocco

    Mohamed Ben Ahmed

  2. Computer Engineering Department, Faculty of Engineering, Karabük University, Karabük, Turkey

    İsmail Rakıp Karaș

  3. CICS.NOVA - Interdisciplinary Centre of Social Sciences, Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal

    Domingos Santos

  4. Department of Sociology of Culture and Communication, Saint Petersburg State University, St. Petersburg, Russia

    Olga Sergeyeva

  5. Faculty of Sciences and Techniques, Association Méditerranéenne des Sciences et Technologies, Tangier, Morocco

    Anouar Abdelhakim Boudhir

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Atik, M.E., Duran, Z. (2021). Deep Learning-Based 3D Face Recognition Using Derived Features from Point Cloud. In: Ben Ahmed, M., Rakıp Karaș, İ., Santos, D., Sergeyeva, O., Boudhir, A.A. (eds) Innovations in Smart Cities Applications Volume 4. SCA 2020. Lecture Notes in Networks and Systems, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-030-66840-2_60

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  • DOI: https://doi.org/10.1007/978-3-030-66840-2_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66839-6

  • Online ISBN: 978-3-030-66840-2

  • eBook Packages: EngineeringEngineering (R0)

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