A Hand Gesture Recognition Method using Inertial Sensor for Rapid Operation on Embedded Device
- Authors
- Lee, Sangyub; Lee, Jaekyu; Cho, Hyeonjoong
- Issue Date
- 29-2월-2020
- Publisher
- KSII-KOR SOC INTERNET INFORMATION
- Keywords
- Pattern recognition; hand gesture recognition; motion recognition; inter-correlation matching; HUD; IMU sensor; wearable device
- Citation
- KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, v.14, no.2, pp.757 - 770
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
- Volume
- 14
- Number
- 2
- Start Page
- 757
- End Page
- 770
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/57598
- DOI
- 10.3837/tiis.2020.02.016
- ISSN
- 1976-7277
- Abstract
- We propose a hand gesture recognition method that is compatible with a head-up display (HUD) including small processing resource. For fast link adaptation with HUD, it is necessary to rapidly process gesture recognition and send the minimum amount of driver hand gesture data from the wearable device. Therefore, we use a method that recognizes each hand gesture with an inertial measurement unit (IMU) sensor based on revised correlation matching. The method of gesture recognition is executed by calculating the correlation between every axis of the acquired data set. By classifying pre-defined gesture values and actions, the proposed method enables rapid recognition. Furthermore, we evaluate the performance of the algorithm, which can be implanted within wearable bands, requiring a minimal process load. The experimental results evaluated the feasibility and effectiveness of our decomposed correlation matching method. Furthermore, we tested the proposed algorithm to confirm the effectiveness of the system using pre-defined gestures of specific motions with a wearable platform device. The experimental results validated the feasibility and effectiveness of the proposed hand gesture recognition system. Despite being based on a very simple concept, the proposed algorithm showed good performance in recognition accuracy
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - Graduate School > Department of Computer and Information Science > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.