Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition
Gesture recognition is a mechanism by which a system recognizes an expressive and purposeful action made by a user’s body. Hand-gesture recognition (HGR) is a staple piece of gesture-recognition literature and has been keenly researched over the past 40 years. Over this time, HGR solutions have vari...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/12/5462 |
| _version_ | 1827735697902010368 |
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| author | Siavash Khaksar Luke Checker Bita Borazjan Iain Murray |
| author_facet | Siavash Khaksar Luke Checker Bita Borazjan Iain Murray |
| author_sort | Siavash Khaksar |
| collection | DOAJ |
| description | Gesture recognition is a mechanism by which a system recognizes an expressive and purposeful action made by a user’s body. Hand-gesture recognition (HGR) is a staple piece of gesture-recognition literature and has been keenly researched over the past 40 years. Over this time, HGR solutions have varied in medium, method, and application. Modern developments in the areas of machine perception have seen the rise of single-camera, skeletal model, hand-gesture identification algorithms, such as media pipe hands (MPH). This paper evaluates the applicability of these modern HGR algorithms within the context of alternative control. Specifically, this is achieved through the development of an HGR-based alternative-control system capable of controlling of a quad-rotor drone. The technical importance of this paper stems from the results produced during the novel and clinically sound evaluation of MPH, alongside the investigatory framework used to develop the final HGR algorithm. The evaluation of MPH highlighted the Z-axis instability of its modelling system which reduced the landmark accuracy of its output from 86.7% to 41.5%. The selection of an appropriate classifier complimented the computationally lightweight nature of MPH whilst compensating for its instability, achieving a classification accuracy of 96.25% for eight single-hand static gestures. The success of the developed HGR algorithm ensured that the proposed alternative-control system could facilitate intuitive, computationally inexpensive, and repeatable drone control without requiring specialised equipment. |
| first_indexed | 2024-03-11T01:57:26Z |
| format | Article |
| id | doaj.art-d66c6c70d26e4f11babd29f5496b39ab |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T01:57:26Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d66c6c70d26e4f11babd29f5496b39ab2023-11-18T12:31:24ZengMDPI AGSensors1424-82202023-06-012312546210.3390/s23125462Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture RecognitionSiavash Khaksar0Luke Checker1Bita Borazjan2Iain Murray3School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Bentley, WA 6102, AustraliaSchool of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Bentley, WA 6102, AustraliaSchool of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Bentley, WA 6102, AustraliaSchool of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Bentley, WA 6102, AustraliaGesture recognition is a mechanism by which a system recognizes an expressive and purposeful action made by a user’s body. Hand-gesture recognition (HGR) is a staple piece of gesture-recognition literature and has been keenly researched over the past 40 years. Over this time, HGR solutions have varied in medium, method, and application. Modern developments in the areas of machine perception have seen the rise of single-camera, skeletal model, hand-gesture identification algorithms, such as media pipe hands (MPH). This paper evaluates the applicability of these modern HGR algorithms within the context of alternative control. Specifically, this is achieved through the development of an HGR-based alternative-control system capable of controlling of a quad-rotor drone. The technical importance of this paper stems from the results produced during the novel and clinically sound evaluation of MPH, alongside the investigatory framework used to develop the final HGR algorithm. The evaluation of MPH highlighted the Z-axis instability of its modelling system which reduced the landmark accuracy of its output from 86.7% to 41.5%. The selection of an appropriate classifier complimented the computationally lightweight nature of MPH whilst compensating for its instability, achieving a classification accuracy of 96.25% for eight single-hand static gestures. The success of the developed HGR algorithm ensured that the proposed alternative-control system could facilitate intuitive, computationally inexpensive, and repeatable drone control without requiring specialised equipment.https://www.mdpi.com/1424-8220/23/12/5462alternative controlfinger trackinghuman computer interface (HCI)hand gesture recognition (HGR)media pipe hands (MPH) |
| spellingShingle | Siavash Khaksar Luke Checker Bita Borazjan Iain Murray Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition Sensors alternative control finger tracking human computer interface (HCI) hand gesture recognition (HGR) media pipe hands (MPH) |
| title | Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition |
| title_full | Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition |
| title_fullStr | Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition |
| title_full_unstemmed | Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition |
| title_short | Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition |
| title_sort | design and evaluation of an alternative control for a quad rotor drone using hand gesture recognition |
| topic | alternative control finger tracking human computer interface (HCI) hand gesture recognition (HGR) media pipe hands (MPH) |
| url | https://www.mdpi.com/1424-8220/23/12/5462 |
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