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Face Recognition Using 3D CNNs

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Data Science

Part of the book series: Transactions on Computer Systems and Networks ((TCSN))

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Abstract

The area of face recognition is one of the most widely researched areas in the domain of computer vision and biometric. This is because the non-intrusive nature of face biometric makes it comparatively more suitable for application in area of surveillance at public places such as airports. The application of primitive methods in face recognition could not give very satisfactory performance. However, with the advent of machine and deep learning methods and their application in face recognition, several major breakthroughs were obtained. The use of 2D convolution neural networks(2D CNN) in face recognition crossed the human face recognition accuracy and reached to 99%. Still, robust face recognition in the presence of real-world conditions such as variation in resolution, illumination and pose is a major challenge for researchers in face recognition. In this work, we used video as input to the 3D CNN architectures for capturing both spatial and time domain information from the video for face recognition in real-world environment. For the purpose of experimentation, we have developed our own video dataset called CVBL video dataset. The use of 3D CNN for face recognition in videos shows promising results with DenseNets performing the best with an accuracy of 97% on CVBL dataset.

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Authors and Affiliations

  1. Computer Vision and Biometric Lab, IIIT Allahabad, Allahabad, India

    Nayaneesh Kumar Mishra & Satish Kumar Singh

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  1. Nayaneesh Kumar Mishra
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  2. Satish Kumar Singh
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Editors and Affiliations

  1. Department of Computer Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India

    Gyanendra K. Verma

  2. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, India

    Badal Soni

  3. Multidimensional Signal Processing Group, Ecole Centrale Marseille, MARSEILLE, France

    Salah Bourennane

  4. Mathematics and Computing Institute, Universidade Federal de Itajuba, Itajuba, Brazil

    Alexandre C. B. Ramos

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Mishra, N.K., Singh, S.K. (2021). Face Recognition Using 3D CNNs. In: Verma, G.K., Soni, B., Bourennane, S., Ramos, A.C.B. (eds) Data Science. Transactions on Computer Systems and Networks. Springer, Singapore. https://doi.org/10.1007/978-981-16-1681-5_18

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  • DOI: https://doi.org/10.1007/978-981-16-1681-5_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1680-8

  • Online ISBN: 978-981-16-1681-5

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