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A Survey: Approaches to Facial Detection and Recognition with Machine Learning Techniques

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Proceedings of Second Doctoral Symposium on Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1374))

Abstract

The present scenario in biometrics is very complex and challenging to classify the facial recognition and authentication. This article described a detailed review on machine learning. Author describes different databases and multiple approaches to overcome the issue of face identification and recognition. This paper offers a description of the work of numerous researchers on the recognition of faces and identity. It focuses on the facial recognition and recognition method in which minimal and unregulated faces processed for individual photographs, and videos are recognized and authenticated. Author describes several facial files, real-time pictures, and videos to discuss sophisticated approaches for their identification and recognition applications. The introduction of a machine learning approach with multiple image datasets also increases the efficiency of the classifier in order to predict face detection and recognition-related content. In conclusion, author elaborated the various approaches of machine learning and deep learning related to facial recognition and identification.

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Author information

Authors and Affiliations

  1. Babu Banarasi Das University, Lucknow, U.P, India

    Prateek Singhal & Prabhat Kumar Srivastava

  2. Kamal Nehru Institute of Technology, Sultanpur, U.P, India

    Arvind Kumar Tiwari

  3. Dr. APJ Abdul Kalam Technical University, Lucknow, U.P, India

    Ratnesh Kumar Shukla

Authors
  1. Prateek Singhal
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  2. Prabhat Kumar Srivastava
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  3. Arvind Kumar Tiwari
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  4. Ratnesh Kumar Shukla
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Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  2. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Ashish Khanna

  3. Institute of Engineering and Technology, Lucknow, Uttar Pradesh, India

    Vineet Kansal

  4. University of Calabria, Rende, Cosenza, Italy

    Giancarlo Fortino

  5. Department of Information Technology, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Singhal, P., Srivastava, P.K., Tiwari, A.K., Shukla, R.K. (2022). A Survey: Approaches to Facial Detection and Recognition with Machine Learning Techniques. In: Gupta, D., Khanna, A., Kansal, V., Fortino, G., Hassanien, A.E. (eds) Proceedings of Second Doctoral Symposium on Computational Intelligence . Advances in Intelligent Systems and Computing, vol 1374. Springer, Singapore. https://doi.org/10.1007/978-981-16-3346-1_9

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