PCA & HMM Based Arm Gesture Recognition Using Inertial Measurement Unit
文献类型：会议论文
| 作者 | Zhang YL(张吟龙) ; Liang W(梁炜); Tan JD(谈金东); Li Y(李杨); Zeng ZM(曾子铭)
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| 出版日期 | 2013 |
| 会议名称 | 8th International Conference on Body Area Networks |
| 会议日期 | September 30 - October 2, 2013 |
| 会议地点 | Boston, MA, USA |
| 关键词 | Principal Component Analysis Hidden Markov Model Arm Gesture Recognition Inertial Measurement Unit |
| 页码 | 193-196 |
| 中文摘要 | This paper presents a novel arm gesture recognition approach that is capable of recognizing seven commonly used sequential arm gestures based upon the outputs from Inertial Measurement Unit (IMU) integrated with 3-D accelerometer and 3-D gyroscope. Unlike the traditional gesture recognition methods where the states in the gesture sequence are irrelevant, our proposed recognition system is intentionally designed to recognize the meaningful gesture sequence where each gesture state relates to the contiguous states which is applicable in the specific occasions such as the police directing the traffic and the arm-injured patients performing a set of arm gestures for effective rehabilitation. In the proposed arm gesture recognition system, the waveforms of the inertial outputs, i.e., 3-D accelerations and 3-D angular rates are automatically segmented for each arm gesture trace at first. Then we employ the Principal Component Analysis (PCA) - a computationally efficient feature selection method characteristic of compressing the inertial data and minimizing the influences of gesture variations. These selected features from PCA are compared with those standard features stored in pattern templates to acquire the gesture observation sequence that satisfy the Markov property. Finally, the Hidden Markov Model is applied in deducing the most likely arm gesture sequence. The experimental results show that our arm gesture classifier achieves up to 93% accuracy. By comparing with the other published recognition methods, our approach verifies the robustness and feasibility in arm gesture recognition using wearable MEMS sensors. |
| 收录类别 | EI |
| 产权排序 | 1 |
| 会议录 | Proceedings of the 8th International Conference on Body Area Networks
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| 会议录出版者 | ACM |
| 会议录出版地 | Brussels, Belgium |
| 语种 | 英语 |
| ISBN号 | 978-1-936968-89-3 |
| 源URL | [http://ir.sia.cn/handle/173321/14581]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 推荐引用方式 GB/T 7714 | Zhang YL,Liang W,Tan JD,et al. PCA & HMM Based Arm Gesture Recognition Using Inertial Measurement Unit[C]. 见:8th International Conference on Body Area Networks. Boston, MA, USA. September 30 - October 2, 2013. |
入库方式： OAI收割
来源：沈阳自动化研究所
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