Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera
學年 107
學期 2
出版（發表）日期 2019-02-04
作品名稱 Real-Time Musical Conducting Gesture Recognition Based on a Dynamic Time Warping Classifier Using a Single-Depth Camera
作品名稱（其他語言）
著者 C. S. Fahn; S. E. Lee; M. L. Wu
單位
出版者
著錄名稱、卷期、頁數 Applied Sciences 9(3), pp. 528-538
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.
關鍵字 human–computer interaction;dynamic gesture recognition;depth camera;palm tracking;dynamic time warping;musical gesture;musical conductor
語言 en
ISSN 2076-3417
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 CHE
公開徵稿
出版型式 ,電子版,紙本
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