SonicFace

Author:

Gao Yang1,Jin Yincheng2,Choi Seokmin3,Li Jiyang3,Pan Junjie4,Shu Lin5,Zhou Chi6,Jin Zhanpeng3

Affiliation:

1. Northwestern University, Department of Computer Science, USA

2. The State University of New York at Buffalo, Department of Computer Science and Engineering, Buffalo, NY, USA

3. The State University of New York at Buffalo, Department of Computer Science and Engineering, USA

4. South China University of Technology, School of Electronic and Information Engineering, China

5. South China University of Technology, School of Future Technology, School of Electronic and Information Engineering, China

6. The State University of New York at Buffalo, Department of Industrial and Systems Engineering, USA

Abstract

Accurate recognition of facial expressions and emotional gestures is promising to understand the audience's feedback and engagement on the entertainment content. Existing methods are primarily based on various cameras or wearable sensors, which either raise privacy concerns or demand extra devices. To this aim, we propose a novel ubiquitous sensing system based on the commodity microphone array --- SonicFace, which provides an accessible, unobtrusive, contact-free, and privacy-preserving solution to monitor the user's emotional expressions continuously without playing hearable sound. SonicFace utilizes a pair of speaker and microphone array to recognize various fine-grained facial expressions and emotional hand gestures by emitted ultrasound and received echoes. Based on a set of experimental evaluations, the accuracy of recognizing 6 common facial expressions and 4 emotional gestures can reach around 80%. Besides, the extensive system evaluations with distinct configurations and an extended real-life case study have demonstrated the robustness and generalizability of the proposed SonicFace system.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Reference91 articles.

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1. I Am an Earphone and I Can Hear My User’s Face: Facial Landmark Tracking Using Smart Earphones;ACM Transactions on Internet of Things;2023-12-16

2. SignRing;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2023-09-27

3. Utilising Emotion Monitoring for Developing Music Interventions for People with Dementia: A State-of-the-Art Review;Sensors;2023-06-22

4. FacER: Contrastive Attention based Expression Recognition via Smartphone Earpiece Speaker;IEEE INFOCOM 2023 - IEEE Conference on Computer Communications;2023-05-17

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