Abstract
Through recent years, facial recognition technology has become increasingly relevant in a widespread area of applications. There are numerous approaches to facial recognition technology, each best-suited for different types of practices. A survey which compares the infrared, thermal, and deep learning methods is performed in this study. Each method is evaluated based on its speed, accuracy, and efficiency and is given a overall percentage of reliability. Further, we examine the advantages and disadvantages of each method and assess what common usage of each method would be in a practical setting. We find a point of commonality between each method type where accuracy and efficiency must strike a balance, further compounded by the practical applications of each method. Our findings show that while there is an ideal method of facial recognition for each individual application, there is no ideal method that applies to every application.
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Muskopf-Stone, N., Votta, G., Van Essen, J., Peregrino, A., Khan Mohd, T. (2022). Facial Recognition Technologies: A Survey and Comparison of Systems and Practical Applications. In: Kim, JH., Singh, M., Khan, J., Tiwary, U.S., Sur, M., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2021. Lecture Notes in Computer Science, vol 13184. Springer, Cham. https://doi.org/10.1007/978-3-030-98404-5_5
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DOI: https://doi.org/10.1007/978-3-030-98404-5_5
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