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Real-Time 3-D Motion Gesture Recognition using Kinect2 as Basis for Traditional Dance Scripting

机译:使用Kinect2作为传统舞蹈脚本编写基础的实时3-D运动手势识别

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This preliminary study presents a system capable of recognizing human gesture in real-time. The gesture is acquired from a Kinect2 sensor which provides skeleton joints represented by three-dimensional coordinate points. The model set consists of eight motion gestures is provided for basis of gesture recognition using Dynamic Time Warping (DTW) algorithm. DTW algorithm is utilized to identify in real time manner by measuring the shortest combined distances in x, y, and z coordinates in order to determined the matched gesture. It can be shown that the system is able to recognize these 8 motions in real time with some limitations. The findings of the this study will provide solid foundation of further research in which the ultimate goal of the research is to create system to automatically recognize sequence of motions in Indonesian traditional dances and convert them into standardized Resource Description Framework (RDF) scripts for the purpose of preserving these dances.
机译:这项初步研究提出了一种能够实时识别人的手势的系统。该手势是从Kinect2传感器获取的,该传感器提供由三维坐标点表示的骨骼关节。提供了由八个运动手势组成的模型集,以使用动态时间规整(DTW)算法进行手势识别。 DTW算法用于通过在x,y和z坐标中测量最短的组合距离来实时识别,以便确定匹配的手势。可以证明,该系统能够实时识别这8个运动,但有一些限制。这项研究的结果将为进一步的研究奠定坚实的基础,该研究的最终目标是创建一种系统,以自动识别印度尼西亚传统舞蹈中的动作序列并将其转换为标准的资源描述框架(RDF)脚本保存这些舞蹈。

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