A²FinPose: An Artificial Intelligence and Augmented Reality-Based Finger Gesture Recognition System for the Human-Machine Interface of Head-mounted Near-Eye Displays
- Resource Type
- Conference
- Authors
- Chang, Wan-Jung; Wu, Pei-Yi; Chen, Yi-Jia; Su, Jian-Ping; Lee, Shih-Hsiung; Chen, Ming-Che
- Source
- 2024 IEEE International Conference on Consumer Electronics (ICCE) Consumer Electronics (ICCE), 2024 IEEE International Conference on. :1-5 Jan, 2024
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
General Topics for Engineers
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Signal Processing and Analysis
Transportation
Human computer interaction
Human-machine systems
Fingers
Gesture recognition
Skeleton
Artificial intelligence
Consumer electronics
Finger Gesture Recognition
Head-Mounted Near-Eye Display
Augmented Reality
Artificial Intelligence
- Language
- ISSN
- 2158-4001
This paper proposes a novel finger gesture recognition system based on Artificial Intelligence (AI) and Augmented Reality (AR) technologies. Designated as A 2 FinPose, this system utilizes finger skeleton movements to identify a range of finger gestures. Our experimental results show that the A 2 FinPose can accurately recognize Gesture-Based Interaction (GBI) and Physics-Based Interaction (PBI) finger gestures, which can facilitate a highly natural human-computer interaction experience for users of head-mounted near-eye display devices.