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Development of a Universal Validation Protocol and an Open-Source Database for Multi-Contextual Facial Expression Recognition.
La Monica, Ludovica; Cenerini, Costanza; Vollero, Luca; Pennazza, Giorgio; Santonico, Marco; Keller, Flavio.
Afiliação
  • La Monica L; Department of Engineering, Unit of Computational Systems and Bioinformatics, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
  • Cenerini C; Department of Engineering, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
  • Vollero L; Department of Engineering, Unit of Computational Systems and Bioinformatics, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
  • Pennazza G; Department of Engineering, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
  • Santonico M; Department of Science and Technology for Sustainable Development and One Health, Unit of Electronics for Sensor Systems, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
  • Keller F; Department of Medicine, Unit of Developmental Neuroscience, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
Sensors (Basel) ; 23(20)2023 Oct 10.
Article em En | MEDLINE | ID: mdl-37896470
ABSTRACT
Facial expression recognition (FER) poses a complex challenge due to diverse factors such as facial morphology variations, lighting conditions, and cultural nuances in emotion representation. To address these hurdles, specific FER algorithms leverage advanced data analysis for inferring emotional states from facial expressions. In this study, we introduce a universal validation methodology assessing any FER algorithm's performance through a web application where subjects respond to emotive images. We present the labelled data database, FeelPix, generated from facial landmark coordinates during FER algorithm validation. FeelPix is available to train and test generic FER algorithms, accurately identifying users' facial expressions. A testing algorithm classifies emotions based on FeelPix data, ensuring its reliability. Designed as a computationally lightweight solution, it finds applications in online systems. Our contribution improves facial expression recognition, enabling the identification and interpretation of emotions associated with facial expressions, offering profound insights into individuals' emotional reactions. This contribution has implications for healthcare, security, human-computer interaction, and entertainment.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Reconhecimento Facial Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Reconhecimento Facial Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Itália