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PŘINOSIL, J. MALÝ, O.
Originální název
Detecting Faces With Face Masks
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
This paper deals with the evaluation of several methods for face detection when the face is covered by a mask. The methods evaluated are Haar cascade and Histogram of Oriented Gradients as feature-based approaches, Multitask Cascade Convolutional Neural Network, Max Margin Object Detection and TinyFace as convolutional neural network based approaches. Various types of face masks are considered: disposal face mask, burka, balaclava, ski helmet with ski goggles, hockey helmet with protective grill, costumes, and others. The TinyFace method achieves the best accuracy result, but also requires much more computational power than other approaches. Therefore, this paper describes an experiment to see if the accuracy of some of the remaining methods can be improved by retraining their models with new image data containing faces with various face masks.
Klíčová slova
face detection, facial mask, convolutional networks, mask categories
Autoři
PŘINOSIL, J.; MALÝ, O.
Vydáno
28. 7. 2021
ISBN
978-1-6654-2933-7
Kniha
2021 44th International Conference on Telecommunications and Signal Processing (TSP)
Strany od
259
Strany do
262
Strany počet
4
URL
https://ieeexplore.ieee.org/document/9522677
BibTex
@inproceedings{BUT175496, author="Jiří {Přinosil} and Ondřej {Malý}", title="Detecting Faces With Face Masks", booktitle="2021 44th International Conference on Telecommunications and Signal Processing (TSP)", year="2021", pages="259--262", doi="10.1109/TSP52935.2021.9522677", isbn="978-1-6654-2933-7", url="https://ieeexplore.ieee.org/document/9522677" }