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A Hand Gesture Recognition Method using Inertial Sensor for Rapid Operation on Embedded Device

  • Lee, Sangyub (Embedded SW Research R&D Center, Korea Electronics Technology Institute) ;
  • Lee, Jaekyu (Embedded SW Research R&D Center, Korea Electronics Technology Institute) ;
  • Cho, Hyeonjoong (Department of Computer and Information Science, Korea University)
  • Received : 2019.09.02
  • Accepted : 2019.11.19
  • Published : 2020.02.29

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.

Acknowledgement

Grant : Development wearable device and services for industrial convergence that support intelligent drivers's ADAS system

Supported by : KEIT

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