Summary of Facial Expression Analysis and Its Potentials in Iot Systems: a Contemporary Survey, by Zixuan Shanggua and Yanjie Dong and Song Guo and Victor C. M. Leung and M. Jamal Deen and Xiping Hu
Facial Expression Analysis and Its Potentials in IoT Systems: A Contemporary Survey
by Zixuan Shanggua, Yanjie Dong, Song Guo, Victor C. M. Leung, M. Jamal Deen, Xiping Hu
First submitted to arxiv on: 23 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach integrates facial expression analysis with Internet-of-Things (IoT) systems to revolutionize real-time emotion recognition in smart healthcare and smart security. The paper discusses the distinctions between macro-expressions (MaEs) and micro-expressions (MiEs), highlighting MaEs’ voluntary nature and MiEs’ involuntary and rapid characteristics. IoT-enhanced MaE analysis enables improved mental health care, while IoT-based MiE detection enhances surveillance accuracy. This work explores advancements in facial expression techniques across various learning paradigms, examining potential applications in healthcare, security, and beyond. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Facial expressions can reveal emotions, with macro-expressions (MaEs) being voluntary and easy to recognize, and micro-expressions (MiEs) being involuntary and revealing concealed emotions. This paper looks at how integrating facial expression analysis with the Internet-of-Things (IoT) can help in smart healthcare and security. It shows how this integration can improve mental health care by monitoring patient emotions, and enhance surveillance accuracy by detecting hidden emotions. |
Keywords
» Artificial intelligence » Mae
