Home Appliance Operation via 3D Keypoint Based Gesture Detection in Body-Relative Command Spaces

In this paper, we propose a flexible device control method using personalized command spaces that function as buttons on a virtual remote control that follows the user. By performing two different gestures in each space, the users can control various devices in a room. This system is implemented through multiple cameras and 3D human keypoint tracking. We experimentally evaluated the influence of command spaces arrangement on gesture recognition and determined the recognition accuracies for different gestures in each command space. The system demonstrated high usability, with even inexperienced users achieving high gesture recognition accuracy.

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Publication Details

Journal
International Journal of Automation Technology
Published
2025-05-04
DOI
https://doi.org/10.20965/ijat.2025.p0216
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Home Appliance Operation via 3D Keypoint Based Gesture Detection in Body-Relative Command Spaces

Sarthak Pathak, Yoshiyuki Mochizuki, Kazunori Umeda, Soichiro Majima et al.
International Journal of Automation Technology
Hand Gesture Recognition Systems
article

Home Appliance Operation via 3D Keypoint Based Gesture Detection in Body-Relative Command Spaces

Sarthak Pathak, Yoshiyuki Mochizuki, Kazunori Umeda, Soichiro Majima, M. Yokota
article en

Abstract

In this paper, we propose a flexible device control method using personalized command spaces that function as buttons on a virtual remote control that follows the user. By performing two different gestures in each space, the users can control various devices in a room. This system is implemented through multiple cameras and 3D human keypoint tracking. We experimentally evaluated the influence of command spaces arrangement on gesture recognition and determined the recognition accuracies for different gestures in each command space. The system demonstrated high usability, with even inexperienced users achieving high gesture recognition accuracy.

International Journal of Automation TechnologyVol. 19(3)
Chuo University (JP)
Openalex Percentile: Top 92%
Hand Gesture Recognition Systems
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