Explaining Facial Expression Recognition
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866908471947952128 |
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| author | Nahulanthran, Sanjeev Tian, Leimin Kulić, Dana Vered, Mor |
| author_facet | Nahulanthran, Sanjeev Tian, Leimin Kulić, Dana Vered, Mor |
| contents | Facial expression recognition (FER) has emerged as a promising approach to the development of emotion-aware intelligent agents and systems. However, key challenges remain in utilizing FER in real-world contexts, including ensuring user understanding and establishing a suitable level of user trust. We developed a novel explanation method utilizing Facial Action Units (FAUs) to explain the output of a FER model through both textual and visual modalities. We conducted an empirical user study evaluating user understanding and trust, comparing our approach to state-of-the-art eXplainable AI (XAI) methods. Our results indicate that visual AND textual as well as textual-only FAU-based explanations resulted in better user understanding of the FER model. We also show that all modalities of FAU-based methods improved appropriate trust of the users towards the FER model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_15864 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Explaining Facial Expression Recognition Nahulanthran, Sanjeev Tian, Leimin Kulić, Dana Vered, Mor Human-Computer Interaction Facial expression recognition (FER) has emerged as a promising approach to the development of emotion-aware intelligent agents and systems. However, key challenges remain in utilizing FER in real-world contexts, including ensuring user understanding and establishing a suitable level of user trust. We developed a novel explanation method utilizing Facial Action Units (FAUs) to explain the output of a FER model through both textual and visual modalities. We conducted an empirical user study evaluating user understanding and trust, comparing our approach to state-of-the-art eXplainable AI (XAI) methods. Our results indicate that visual AND textual as well as textual-only FAU-based explanations resulted in better user understanding of the FER model. We also show that all modalities of FAU-based methods improved appropriate trust of the users towards the FER model. |
| title | Explaining Facial Expression Recognition |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2501.15864 |