Application of Texture Descriptors to Facial Emotion Recognition in Infants
The recognition of facial emotions is an important issue in computer vision and artificial intelligence due to its important academic and commercial potential. If we focus on the health sector, the ability to detect and control patients’ emotions, mainly pain, is a fundamental objective wi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/10/3/1115 |
| _version_ | 1828756824380145664 |
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| author | Ana Martínez Francisco A. Pujol Higinio Mora |
| author_facet | Ana Martínez Francisco A. Pujol Higinio Mora |
| author_sort | Ana Martínez |
| collection | DOAJ |
| description | The recognition of facial emotions is an important issue in computer vision and artificial intelligence due to its important academic and commercial potential. If we focus on the health sector, the ability to detect and control patients’ emotions, mainly pain, is a fundamental objective within any medical service. Nowadays, the evaluation of pain in patients depends mainly on the continuous monitoring of the medical staff when the patient is unable to express verbally his/her experience of pain, as is the case of patients under sedation or babies. Therefore, it is necessary to provide alternative methods for its evaluation and detection. Facial expressions can be considered as a valid indicator of a person’s degree of pain. Consequently, this paper presents a monitoring system for babies that uses an automatic pain detection system by means of image analysis. This system could be accessed through wearable or mobile devices. To do this, this paper makes use of three different texture descriptors for pain detection: Local Binary Patterns, Local Ternary Patterns, and Radon Barcodes. These descriptors are used together with Support Vector Machines (SVM) for their classification. The experimental results show that the proposed features give a very promising classification accuracy of around 95% for the Infant COPE database, which proves the validity of the proposed method. |
| first_indexed | 2024-12-10T23:22:29Z |
| format | Article |
| id | doaj.art-c1c395cfb86248c395ac85336b4246a3 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-10T23:22:29Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-c1c395cfb86248c395ac85336b4246a32022-12-22T01:29:41ZengMDPI AGApplied Sciences2076-34172020-02-01103111510.3390/app10031115app10031115Application of Texture Descriptors to Facial Emotion Recognition in InfantsAna Martínez0Francisco A. Pujol1Higinio Mora2Department of Computer Technology, University of Alicante, 03690 San Vicente del Raspeig-Alicante, SpainDepartment of Computer Technology, University of Alicante, 03690 San Vicente del Raspeig-Alicante, SpainDepartment of Computer Technology, University of Alicante, 03690 San Vicente del Raspeig-Alicante, SpainThe recognition of facial emotions is an important issue in computer vision and artificial intelligence due to its important academic and commercial potential. If we focus on the health sector, the ability to detect and control patients’ emotions, mainly pain, is a fundamental objective within any medical service. Nowadays, the evaluation of pain in patients depends mainly on the continuous monitoring of the medical staff when the patient is unable to express verbally his/her experience of pain, as is the case of patients under sedation or babies. Therefore, it is necessary to provide alternative methods for its evaluation and detection. Facial expressions can be considered as a valid indicator of a person’s degree of pain. Consequently, this paper presents a monitoring system for babies that uses an automatic pain detection system by means of image analysis. This system could be accessed through wearable or mobile devices. To do this, this paper makes use of three different texture descriptors for pain detection: Local Binary Patterns, Local Ternary Patterns, and Radon Barcodes. These descriptors are used together with Support Vector Machines (SVM) for their classification. The experimental results show that the proposed features give a very promising classification accuracy of around 95% for the Infant COPE database, which proves the validity of the proposed method.https://www.mdpi.com/2076-3417/10/3/1115emotion recognitionpattern recognitiontexture descriptorsmobile tool |
| spellingShingle | Ana Martínez Francisco A. Pujol Higinio Mora Application of Texture Descriptors to Facial Emotion Recognition in Infants Applied Sciences emotion recognition pattern recognition texture descriptors mobile tool |
| title | Application of Texture Descriptors to Facial Emotion Recognition in Infants |
| title_full | Application of Texture Descriptors to Facial Emotion Recognition in Infants |
| title_fullStr | Application of Texture Descriptors to Facial Emotion Recognition in Infants |
| title_full_unstemmed | Application of Texture Descriptors to Facial Emotion Recognition in Infants |
| title_short | Application of Texture Descriptors to Facial Emotion Recognition in Infants |
| title_sort | application of texture descriptors to facial emotion recognition in infants |
| topic | emotion recognition pattern recognition texture descriptors mobile tool |
| url | https://www.mdpi.com/2076-3417/10/3/1115 |
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