摘要
针对手势交互中手势信号的相似性和不稳定性,设计实现一种基于三轴加速度传感器的手势识别方案。采用MMA7260加速度传感器采集主手腕的手势动作信号,根据手势加速度信号的特点,进行手势动作数据窗口的自动检测、信号去噪和重采样等预处理,通过提取手势动作的关键特征,构造离散隐马尔可夫模型,实现手势动作识别。实验结果证明该方案的识别精度较高。
Aiming at similarity and instability of gesture activity signal in gesture interaction, a gesture recognition scheme based on three-axial accelerometer is presented. It utilizes a MMA7260 accelerometer to capture the acceleration signal of dominant wrist. An activity detection algorithm is used to auto determine the data stream which containing interesting motion according to the features of gesture activity signal. After denoising and resampling the acceleration data streams, gesture features are extracted, and Discrete Hidden Markov Model（DHMM） is built for gesture recognition. Experimental results demonstrate the effectiveness of the scheme.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第24期141-143,共3页
Computer Engineering
基金
华中师范大学中央高校基本科研业务费基金资助项目(CCNU10A02008)
教育部人文社会科学研究计划基金资助项目(10YJA870026)
关键词
加速度传感器
手势识别
人机交互
信号处理
离散隐马尔可夫模型
accelerometer
gesture recognition
human-computer interaction
signal processing
Discrete Hidden Markov ModeI（DHMM）
