Статья

A NOVEL METHOD FOR PROTECTIVE FACE MASK DETECTION USING CONVOLUTIONAL NEURAL NETWORKS AND IMAGE HISTOGRAMS

E. Ryumina, D. Ryumin, D. Ivanko, A. Karpov,
2021

Abstract. This paper proposes a new hybrid method for automatic detection and recognition of the presence/absence of a protective mask on human's face. It combines visual features extracted using Convolutional Neural Network (CNN) with image histograms that convey information about pixel intensity. Several pre-trained models for building feature extraction systems using a CNN and several types of image histograms are considered in this paper. We test our approach on the Medical Mask Dataset and perform cross-corpus analysis on two other databases named Masked Faces (MAFA) and Real-World Masked Face Dataset (RMFD). We demonstrate that the proposed hybrid method increases the Unweighted Average Recalls (UARs) of recognition of the presence/absence of a protective mask on human's face in comparison with traditional CNNs on the MAFA and RMFD databases by 0.96% and 1.32%, respectively. The proposed method can be generalized and used for other tasks of biometry, computer vision, machine learning and automatic face recognition.

Цитирование

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Версии

  • 1. Version of Record от 2021-04-15

Метаданные

Об авторах
  • E. Ryumina
    St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), St. Petersburg, Russian Federation
  • D. Ryumin
    St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), St. Petersburg, Russian Federation
  • D. Ivanko
    St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), St. Petersburg, Russian Federation
  • A. Karpov
    St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), St. Petersburg, Russian Federation
Название журнала
  • ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Том
  • XLIV-2/W1-2021
Страницы
  • 177-182
Издатель
  • Copernicus Publications
Тип документа
  • journal article
Тип лицензии Creative Commons
  • CC BY
Правовой статус документа
  • Свободная лицензия
Источник
  • dimensions