Accuracy Enhancement of Hand Gesture Recognition Using CNN
Human gestures are immensely significant in human-machine interactions. Complex hand gesture input and noise caused by the external environment must be addressed in order to improve the accuracy of hand gesture recognition algorithms. To overcome this challenge, we employ a combination of 2D-FFT and...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10064302/ |
| _version_ | 1797866186243833856 |
|---|---|
| author | Gyutae Park Vasantha Kumar Chandrasegar Jinhwan Koh |
| author_facet | Gyutae Park Vasantha Kumar Chandrasegar Jinhwan Koh |
| author_sort | Gyutae Park |
| collection | DOAJ |
| description | Human gestures are immensely significant in human-machine interactions. Complex hand gesture input and noise caused by the external environment must be addressed in order to improve the accuracy of hand gesture recognition algorithms. To overcome this challenge, we employ a combination of 2D-FFT and convolutional neural networks (CNN) in this research. The accuracy of human-machine interactions is improved by using Ultra Wide Bandwidth (UWB) radar to acquire image data, then transforming it with 2D-FFT and bringing it into CNN for classification. The classification results of the proposed method revealed that it required less time to learn than prominent models and had similar accuracy. |
| first_indexed | 2024-04-09T23:21:04Z |
| format | Article |
| id | doaj.art-bda90a670d794121b5cee22469216aa4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-09T23:21:04Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-bda90a670d794121b5cee22469216aa42023-03-21T23:00:30ZengIEEEIEEE Access2169-35362023-01-0111264962650110.1109/ACCESS.2023.325453710064302Accuracy Enhancement of Hand Gesture Recognition Using CNNGyutae Park0https://orcid.org/0000-0001-7728-7108Vasantha Kumar Chandrasegar1https://orcid.org/0000-0002-9676-7665Jinhwan Koh2https://orcid.org/0000-0003-2874-9614Department of Electronic Engineering, Gyeongsang National University, Jinju, Gyeongsangnam, South KoreaDepartment of Electronic Engineering, Gyeongsang National University, Jinju, Gyeongsangnam, South KoreaDepartment of Electronic Engineering, Gyeongsang National University, Jinju, Gyeongsangnam, South KoreaHuman gestures are immensely significant in human-machine interactions. Complex hand gesture input and noise caused by the external environment must be addressed in order to improve the accuracy of hand gesture recognition algorithms. To overcome this challenge, we employ a combination of 2D-FFT and convolutional neural networks (CNN) in this research. The accuracy of human-machine interactions is improved by using Ultra Wide Bandwidth (UWB) radar to acquire image data, then transforming it with 2D-FFT and bringing it into CNN for classification. The classification results of the proposed method revealed that it required less time to learn than prominent models and had similar accuracy.https://ieeexplore.ieee.org/document/10064302/Hand gestureCNNdeep learningIR-UWB radar2D-Fast Fourier Transform |
| spellingShingle | Gyutae Park Vasantha Kumar Chandrasegar Jinhwan Koh Accuracy Enhancement of Hand Gesture Recognition Using CNN IEEE Access Hand gesture CNN deep learning IR-UWB radar 2D-Fast Fourier Transform |
| title | Accuracy Enhancement of Hand Gesture Recognition Using CNN |
| title_full | Accuracy Enhancement of Hand Gesture Recognition Using CNN |
| title_fullStr | Accuracy Enhancement of Hand Gesture Recognition Using CNN |
| title_full_unstemmed | Accuracy Enhancement of Hand Gesture Recognition Using CNN |
| title_short | Accuracy Enhancement of Hand Gesture Recognition Using CNN |
| title_sort | accuracy enhancement of hand gesture recognition using cnn |
| topic | Hand gesture CNN deep learning IR-UWB radar 2D-Fast Fourier Transform |
| url | https://ieeexplore.ieee.org/document/10064302/ |
| work_keys_str_mv | AT gyutaepark accuracyenhancementofhandgesturerecognitionusingcnn AT vasanthakumarchandrasegar accuracyenhancementofhandgesturerecognitionusingcnn AT jinhwankoh accuracyenhancementofhandgesturerecognitionusingcnn |