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Detail publikačního výsledku
PŘINOSIL, J.; MALÝ, O.
Originální název
Detecting Faces With Face Masks
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
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.
Anglický abstrakt
Klíčová slova
face detection, facial mask, convolutional networks, mask categories
Klíčová slova v angličtině
Autoři
Rok RIV
2022
Vydáno
28.07.2021
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" }