Macro- and Micro-Expressions Facial Datasets: A Survey
Automatic facial expression recognition is essential for many potential applications. Thus, having a clear overview on existing datasets that have been investigated within the framework of face expression recognition is of paramount importance in designing and evaluating effective solutions, notably...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/4/1524 |
| _version_ | 1797476671835602944 |
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| author | Hajer Guerdelli Claudio Ferrari Walid Barhoumi Haythem Ghazouani Stefano Berretti |
| author_facet | Hajer Guerdelli Claudio Ferrari Walid Barhoumi Haythem Ghazouani Stefano Berretti |
| author_sort | Hajer Guerdelli |
| collection | DOAJ |
| description | Automatic facial expression recognition is essential for many potential applications. Thus, having a clear overview on existing datasets that have been investigated within the framework of face expression recognition is of paramount importance in designing and evaluating effective solutions, notably for neural networks-based training. In this survey, we provide a review of more than eighty facial expression datasets, while taking into account both macro- and micro-expressions. The proposed study is mostly focused on spontaneous and in-the-wild datasets, given the common trend in the research is that of considering contexts where expressions are shown in a spontaneous way and in a real context. We have also provided instances of potential applications of the investigated datasets, while putting into evidence their pros and cons. The proposed survey can help researchers to have a better understanding of the characteristics of the existing datasets, thus facilitating the choice of the data that best suits the particular context of their application. |
| first_indexed | 2024-03-09T21:05:57Z |
| format | Article |
| id | doaj.art-2d24da26881d420fa9ddc867c91edf1c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:05:57Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2d24da26881d420fa9ddc867c91edf1c2023-11-23T22:01:01ZengMDPI AGSensors1424-82202022-02-01224152410.3390/s22041524Macro- and Micro-Expressions Facial Datasets: A SurveyHajer Guerdelli0Claudio Ferrari1Walid Barhoumi2Haythem Ghazouani3Stefano Berretti4Research Team on Intelligent Systems in Imaging and Artificial Vision (SIIVA), LR16ES06 Laboratoire de Recherche en Informatique, Modélisation et Traitement de’Information et dea Connaissance (LIMTIC), Institut Supérieur d’Informatique d’El Manar, Université de Tunis El Manar, Tunis 1068, TunisiaDepartment of Engineering and Architecture, University of Parma, 43121 Parma, ItalyResearch Team on Intelligent Systems in Imaging and Artificial Vision (SIIVA), LR16ES06 Laboratoire de Recherche en Informatique, Modélisation et Traitement de’Information et dea Connaissance (LIMTIC), Institut Supérieur d’Informatique d’El Manar, Université de Tunis El Manar, Tunis 1068, TunisiaResearch Team on Intelligent Systems in Imaging and Artificial Vision (SIIVA), LR16ES06 Laboratoire de Recherche en Informatique, Modélisation et Traitement de’Information et dea Connaissance (LIMTIC), Institut Supérieur d’Informatique d’El Manar, Université de Tunis El Manar, Tunis 1068, TunisiaMedia Integration and Communication Center, University of Florence, 50121 Firenze, ItalyAutomatic facial expression recognition is essential for many potential applications. Thus, having a clear overview on existing datasets that have been investigated within the framework of face expression recognition is of paramount importance in designing and evaluating effective solutions, notably for neural networks-based training. In this survey, we provide a review of more than eighty facial expression datasets, while taking into account both macro- and micro-expressions. The proposed study is mostly focused on spontaneous and in-the-wild datasets, given the common trend in the research is that of considering contexts where expressions are shown in a spontaneous way and in a real context. We have also provided instances of potential applications of the investigated datasets, while putting into evidence their pros and cons. The proposed survey can help researchers to have a better understanding of the characteristics of the existing datasets, thus facilitating the choice of the data that best suits the particular context of their application.https://www.mdpi.com/1424-8220/22/4/1524macro-expressions datasetsmicro-expressions datasetsfacial expression recognitionapplications of facial expression datasets |
| spellingShingle | Hajer Guerdelli Claudio Ferrari Walid Barhoumi Haythem Ghazouani Stefano Berretti Macro- and Micro-Expressions Facial Datasets: A Survey Sensors macro-expressions datasets micro-expressions datasets facial expression recognition applications of facial expression datasets |
| title | Macro- and Micro-Expressions Facial Datasets: A Survey |
| title_full | Macro- and Micro-Expressions Facial Datasets: A Survey |
| title_fullStr | Macro- and Micro-Expressions Facial Datasets: A Survey |
| title_full_unstemmed | Macro- and Micro-Expressions Facial Datasets: A Survey |
| title_short | Macro- and Micro-Expressions Facial Datasets: A Survey |
| title_sort | macro and micro expressions facial datasets a survey |
| topic | macro-expressions datasets micro-expressions datasets facial expression recognition applications of facial expression datasets |
| url | https://www.mdpi.com/1424-8220/22/4/1524 |
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