Smartphone Facial Recognition

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By Kenneth Wu

Note: This page is incomplete.

Facial recognition systems are computer programs that match faces against a database [1]. A trivial task for humans, achieving high levels of accuracy has been difficult for computers until recently.[1] Deep learning [2] through the use of convolutional neural networks [3] currently dominates the facial recognition field.[2] However, deep learning uses much more memory, disk storage, and computational resources than traditional computer vision, presenting significant challenges to facial recognition with the limited hardware capabilities of smartphones.[3] Accordingly, smartphone manufacturers have taken to using processors with dedicated neural engines for deep learning tasks [4] as well as creating simpler and more compact models that mimic the behavior of more complex models.[3]

Model

Facial recognition systems accomplish their tasks by detecting the presence of a face, analyzing its features, and confirming the identity of the person.[5] Training data is fed into a facial detection algorithm, where the two most popular such methods are the Viola-Jones algorithm and the use of convolutional neural networks [6]

History

Applications

References

  1. Brownlee, J. (2019, July 5). A gentle introduction to deep learning for face recognition. Machine Learning Mastery. Retrieved November 14, 2022, from https://machinelearningmastery.com/introduction-to-deep-learning-for-face-recognition/
  2. Almabdy, S., & Elrefaei, L. (2019). Deep convolutional neural network-based approaches for face recognition. Applied Sciences, 9(20), 4397. https://doi.org/10.3390/app9204397
  3. 3.0 3.1 Computer Vision Machine Learning Team. (2017, November). An on-device deep neural network for face detection. Apple Machine Learning Research. Retrieved November 14, 2022, from https://machinelearning.apple.com/research/face-detection#1
  4. Samsung. (2018). Exynos 9810: Mobile Processor. Samsung Semiconductor Global. Retrieved November 14, 2022, from https://semiconductor.samsung.com/processor/mobile-processor/exynos-9-series-9810/
  5. Klosowski, T. (2020, July 15). Facial recognition is everywhere. here's what we can do about it. The New York Times. Retrieved November 14, 2022, from https://www.nytimes.com/wirecutter/blog/how-facial-recognition-works/
  6. Enriquez, K. (2018, May 15). (thesis). Faster face detection using Convolutional Neural Networks & the Viola-Jones algorithm. California State University Stanislaus. Retrieved November 14, 2022, from https://www.csustan.edu/sites/default/files/groups/University%20Honors%20Program/Journals/01_enriquez.pdf.