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Sparse Representation Based Face Recognition Using VGGFace

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Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) (ICMLBDA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 256))

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Abstract

Face recognition is one of the most important applications of computer vision and it has been used in biometric, surveillance cameras and face tagging. Recently, the convolutional neural network (CNN) model has shown better performance on visual data and it attracted more attention due to automatic feature extraction. Sparse representation-based classification (SRC) has been shown tremendous success in the area of face recognition since the last decade. Convolution neural network is invariant to unconstrained variation whereas SRC is prone. SRC needs discriminative features to represent a test sample. This paper, exploits the significance of both the aforementioned methods and proposed a new CNN-SRC which alleviates the performance of unconstraint variation. The experimental results of the proposed method have shown better performance on different benchmark databases.

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Funding

This study was funded by the Ministry of Electronics and Information Technology (India) (Grant No.: MLA/MUM/GA/10(37)B).

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Authors and Affiliations

  1. Visvesvaraya National Institute of Technology, Nagpur, 440010, India

    Jitendra Madarkar & Poonam Sharma

Authors
  1. Jitendra Madarkar
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  2. Poonam Sharma
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Editor information

Editors and Affiliations

  1. Indian Institute of Technology Patna, Patna, India

    Rajiv Misra

  2. Indian Institute of Technology Bombay, Mumbai, India

    Rudrapatna K. Shyamasundar

  3. Indian Institute of Technology (BHU), Varanasi, India

    Amrita Chaturvedi

  4. Cardiff University, Cardiff, UK

    Rana Omer

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Conflict of interest. The authors declare that there are no conflicts of interest regarding the publication of this paper.

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Madarkar, J., Sharma, P. (2022). Sparse Representation Based Face Recognition Using VGGFace. In: Misra, R., Shyamasundar, R.K., Chaturvedi, A., Omer, R. (eds) Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021). ICMLBDA 2021. Lecture Notes in Networks and Systems, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-030-82469-3_25

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