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UIBVFED-Mask: A Dataset for Comparing Facial Expressions with and without Face Masks

Author

Listed:
  • Miquel Mascaró-Oliver

    (Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa, Km. 7.5, 07122 Palma de Mallorca, Spain)

  • Ramon Mas-Sansó

    (Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa, Km. 7.5, 07122 Palma de Mallorca, Spain)

  • Esperança Amengual-Alcover

    (Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa, Km. 7.5, 07122 Palma de Mallorca, Spain)

  • Maria Francesca Roig-Maimó

    (Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa, Km. 7.5, 07122 Palma de Mallorca, Spain)

Abstract

After the COVID-19 pandemic the use of face masks has become a common practice in many situations. Partial occlusion of the face due to the use of masks poses new challenges for facial expression recognition because of the loss of significant facial information. Consequently, the identification and classification of facial expressions can be negatively affected when using neural networks in particular. This paper presents a new dataset of virtual characters, with and without face masks, with identical geometric information and spatial location. This novelty will certainly allow researchers a better refinement on lost information due to the occlusion of the mask.

Suggested Citation

  • Miquel Mascaró-Oliver & Ramon Mas-Sansó & Esperança Amengual-Alcover & Maria Francesca Roig-Maimó, 2023. "UIBVFED-Mask: A Dataset for Comparing Facial Expressions with and without Face Masks," Data, MDPI, vol. 8(1), pages 1-8, January.
    • Handle: RePEc:gam:jdataj:v:8:y:2023:i:1:p:17-:d:1032421
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