Multi-Point Gesture Recognition Leveraging Acoustic Signals and CNN
- Title
- Multi-Point Gesture Recognition Leveraging Acoustic Signals and CNN
- Author
- 윤종원
- Keywords
- Acoustic signal; CIR; CNN; Gesture recognition
- Issue Date
- 2020-10
- Publisher
- IEEE Computer Society
- Citation
- International Conference on ICT Convergence, article no. 9289218, Page. 1699-1704
- Abstract
- With the emergence of smart home appliances and AR/VR content, the demand for a better user interface is constantly increasing. Traditional user interface, touch-based interface is no longer applied to AR/VR applications and vision or RF-based gesture recognition requires camera and sensors, resulting in additional cost. The accuracy of above-mentioned methods highly depends on brightness and surrounding environment, therefore they fail to guarantee robustness. There are several researches on acoustic-based gesture recognition, but are limited to single point movement such as straight line, circle and triangle. In this paper, we design and implement multi-point gesture recognition system utilizing both the acoustic signals and machine learning technique. We use channel impulse response (CIR) containing multi-path information to recognize multi-point gestures, and construct a CNN model to learn its features. In addition, we present a method of constructing a CNN model suitable for gesture recognition. Evaluation results show that our system successfully recognizes multi-point gestures and demonstrate its efficacy. ? 2020 IEEE.
- URI
- https://ieeexplore.ieee.org/document/9289218https://repository.hanyang.ac.kr/handle/20.500.11754/178605
- ISSN
- 2162-1233
- DOI
- 10.1109/ICTC49870.2020.9289218
- Appears in Collections:
- COLLEGE OF COMPUTING[E](소프트웨어융합대학) > COMPUTER SCIENCE(소프트웨어학부) > Articles
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