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Body gesture validation using multi-dimensional dynamic time warping on Kinect data

机译:使用多维动态时间在Kinect数据上翘曲的身体手势验证

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This paper presents a system capable of identifying and validating various human body gestures. Body data is acquired from a Kinect sensor and consist in a set of bones represented by their rotation in 3D space. The main goal is to correctly identify the user performed gesture and return feedback related to its performance accuracy. A database with several samples for each gesture is built and used as ground truth in the gesture validation process. A novel approach of dynamic time warping algorithm is proposed for synchronizing the performed gesture with the corresponding ground truth dataset. If the sequences are not synchronized, feedback is returned to user as a comparison between its performance and the closest sample in the database. Experimental results show high accuracy at about 90% success rate. The system performs better for gestures in which the users' body is fully exposed to the sensor.
机译:本文介绍了一种能够识别和验证各种人体手势的系统。从Kinect传感器获取身体数据,并由其在3D空间中的旋转中表示的一组骨骼组成。主要目标是正确识别用户执行的手势并返回与其性能准确性相关的反馈。构建了每个手势的具有多个样本的数据库,并在手势验证过程中作为地面真实构建。提出了一种动态时间翘曲算法的新方法,用于将执行的手势与相应的地面真理数据集同步。如果序列不同步,则反馈将其作为其性能和数据库中最近的样本之间的比较。实验结果表明了高精度,成功率约为90%。该系统对用户身体完全暴露于传感器的手势更好。

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