Multi-face emotion detection for effective Human-Robot Interaction
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913646258421760 |
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| author | Yahyaoui, Mohamed Ala Oujabour, Mouaad Letaifa, Leila Ben Bohi, Amine |
| author_facet | Yahyaoui, Mohamed Ala Oujabour, Mouaad Letaifa, Leila Ben Bohi, Amine |
| contents | The integration of dialogue interfaces in mobile devices has become ubiquitous, providing a wide array of services. As technology progresses, humanoid robots designed with human-like features to interact effectively with people are gaining prominence, and the use of advanced human-robot dialogue interfaces is continually expanding. In this context, emotion recognition plays a crucial role in enhancing human-robot interaction by enabling robots to understand human intentions. This research proposes a facial emotion detection interface integrated into a mobile humanoid robot, capable of displaying real-time emotions from multiple individuals on a user interface. To this end, various deep neural network models for facial expression recognition were developed and evaluated under consistent computer-based conditions, yielding promising results. Afterwards, a trade-off between accuracy and memory footprint was carefully considered to effectively implement this application on a mobile humanoid robot. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2501_07213 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multi-face emotion detection for effective Human-Robot Interaction Yahyaoui, Mohamed Ala Oujabour, Mouaad Letaifa, Leila Ben Bohi, Amine Human-Computer Interaction Artificial Intelligence Computer Vision and Pattern Recognition Robotics The integration of dialogue interfaces in mobile devices has become ubiquitous, providing a wide array of services. As technology progresses, humanoid robots designed with human-like features to interact effectively with people are gaining prominence, and the use of advanced human-robot dialogue interfaces is continually expanding. In this context, emotion recognition plays a crucial role in enhancing human-robot interaction by enabling robots to understand human intentions. This research proposes a facial emotion detection interface integrated into a mobile humanoid robot, capable of displaying real-time emotions from multiple individuals on a user interface. To this end, various deep neural network models for facial expression recognition were developed and evaluated under consistent computer-based conditions, yielding promising results. Afterwards, a trade-off between accuracy and memory footprint was carefully considered to effectively implement this application on a mobile humanoid robot. |
| title | Multi-face emotion detection for effective Human-Robot Interaction |
| topic | Human-Computer Interaction Artificial Intelligence Computer Vision and Pattern Recognition Robotics |
| url | https://arxiv.org/abs/2501.07213 |