摘要
Facial expression reconstruction technology offers considerable potential in areas like human-computer interaction, affective computing, and virtual reality. To tackle the privacy challenges and environmental constraints inherent in traditional camera-based systems, researchers have recently introduced ear-worn devices as a viable solution. Nevertheless, these methods still demand enhancements, particularly in aspects such as design appeal and energy efficiency, to achieve broader applicability and practical use. This paper introduces a system called IMUFace. It uses inertial measurement units (IMUs) embedded in wireless earphones to detect subtle ear movements caused by facial muscle activities, allowing for covert and low-power facial reconstruction. A user study involving 12 participants was conducted, and a deep learning model named IMUTwinTrans was proposed. The results show that IMUFace can accurately predict users’ facial landmarks with a precision of 2.21 mm, using only five minutes of training data. The predicted landmarks can be utilized to reconstruct a three-dimensional facial model. IMUFace operates at a sampling rate of 30 Hz with a relatively low power consumption of 58 mW. The findings validate the feasibility of IMUFace and highlight potential directions for further research towards its practical adoption in mobile environments.
| 源语言 | 英语 |
|---|---|
| 页(从-至) | 419-435 |
| 页数 | 17 |
| 期刊 | CCF Transactions on Pervasive Computing and Interaction |
| 卷 | 8 |
| 期 | 3 |
| DOI | |
| 出版状态 | 已出版 - 9月 2026 |
| 已对外发布 | 是 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 7 经济适用的清洁能源
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