期刊
SENSORS
卷 20, 期 20, 页码 -出版社
MDPI
DOI: 10.3390/s20205732
关键词
deep learning applications; human perceptual cognition; depth camera; inertial sensor; action recognition; decision level fusion; violin bowing actions
资金
- Ministry of Science and Technology, Taiwan [MOST 107-2221-E-119 -001-MY2, MOST 109-2221-E-119-002]
We propose a violin bowing action recognition system that can accurately recognize distinct bowing actions in classical violin performance. This system can recognize bowing actions by analyzing signals from a depth camera and from inertial sensors that are worn by a violinist. The contribution of this study is threefold: (1) a dataset comprising violin bowing actions was constructed from data captured by a depth camera and multiple inertial sensors; (2) data augmentation was achieved for depth-frame data through rotation in three-dimensional world coordinates and for inertial sensing data through yaw, pitch, and roll angle transformations; and, (3) bowing action classifiers were trained using different modalities, to compensate for the strengths and weaknesses of each modality, based on deep learning methods with a decision-level fusion process. In experiments, large external motions and subtle local motions produced from violin bow manipulations were both accurately recognized by the proposed system (average accuracy > 80%).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据