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| 题名: | Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera |
| 作者: | Fahn, C. S.;Lee, S. E.;Wu, M. L. |
| 关键词: | human–computer interaction;dynamic gesture recognition;depth camera;palm tracking;dynamic time warping;musical gesture;musical conductor |
| 日期: | 2019-02-04 |
| 上传时间: | 2021-03-04 12:13:09 (UTC+8) |
| 出版者: | MDPI |
| 摘要: | Gesture recognition is a human–computer interaction method, which is widely used for educational, medical, and entertainment purposes. Humans also use gestures to communicate with each other, and musical conducting uses gestures in this way. In musical conducting, conductors wave their hands to control the speed and strength of the music played. However, beginners may have a limited comprehension of the gestures and might not be able to properly follow the ensembles. Therefore, this paper proposes a real-time musical conducting gesture recognition system to help music players improve their performance. We used a single-depth camera to capture image inputs and establish a real-time dynamic gesture recognition system. The Kinect software development kit created a skeleton model by capturing the palm position. Different palm gestures were collected to develop training templates for musical conducting. The dynamic time warping algorithm was applied to recognize the different conducting gestures at various conducting speeds, thereby achieving real-time dynamic musical conducting gesture recognition. In the experiment, we used 5600 examples of three basic types of musical conducting gestures, including seven capturing angles and five performing speeds for evaluation. The experimental result showed that the average accuracy was 89.17% in 30 frames per second. |
| 關聯: | Applied Sciences 9(3), pp. 528-538 |
| DOI: | 10.3390/app9030528 |
| 显示于类别: | [資訊工程學系暨研究所] 期刊論文
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