Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System
In this study, we propose the gesture recognition algorithm using support vector machines (SVM) and histogram of oriented gradient (HOG). Besides, we also use the CNN model to classify gestures. We approach and select techniques of applying problem controlling for the robotic system. The goal of the...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2021/3986497 |
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| _version_ | 1832546074738294784 |
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| author | Phat Nguyen Huu Tan Phung Ngoc |
| author_facet | Phat Nguyen Huu Tan Phung Ngoc |
| author_sort | Phat Nguyen Huu |
| collection | DOAJ |
| description | In this study, we propose the gesture recognition algorithm using support vector machines (SVM) and histogram of oriented gradient (HOG). Besides, we also use the CNN model to classify gestures. We approach and select techniques of applying problem controlling for the robotic system. The goal of the algorithm is to detect gestures with real-time processing speed, minimize interference, and reduce the ability to capture unintentional gestures. Static gesture controls are used in this study including on, off, increasing, and decreasing. Besides, it uses motion gestures including turning on the status switch and increasing and decreasing the volume. Results show that the algorithm is up to 99% accuracy with a 70-millisecond execution time per frame that is suitable for industrial applications. |
| format | Article |
| id | doaj-art-a4759bfe7d2d4a2487f0d0b6818a067a |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-a4759bfe7d2d4a2487f0d0b6818a067a2025-02-03T07:23:57ZengWileyJournal of Robotics1687-96001687-96192021-01-01202110.1155/2021/39864973986497Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic SystemPhat Nguyen Huu0Tan Phung Ngoc1School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, VietnamSchool of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, VietnamIn this study, we propose the gesture recognition algorithm using support vector machines (SVM) and histogram of oriented gradient (HOG). Besides, we also use the CNN model to classify gestures. We approach and select techniques of applying problem controlling for the robotic system. The goal of the algorithm is to detect gestures with real-time processing speed, minimize interference, and reduce the ability to capture unintentional gestures. Static gesture controls are used in this study including on, off, increasing, and decreasing. Besides, it uses motion gestures including turning on the status switch and increasing and decreasing the volume. Results show that the algorithm is up to 99% accuracy with a 70-millisecond execution time per frame that is suitable for industrial applications.http://dx.doi.org/10.1155/2021/3986497 |
| spellingShingle | Phat Nguyen Huu Tan Phung Ngoc Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System Journal of Robotics |
| title | Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System |
| title_full | Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System |
| title_fullStr | Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System |
| title_full_unstemmed | Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System |
| title_short | Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System |
| title_sort | hand gesture recognition algorithm using svm and hog model for control of robotic system |
| url | http://dx.doi.org/10.1155/2021/3986497 |
| work_keys_str_mv | AT phatnguyenhuu handgesturerecognitionalgorithmusingsvmandhogmodelforcontrolofroboticsystem AT tanphungngoc handgesturerecognitionalgorithmusingsvmandhogmodelforcontrolofroboticsystem |