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首页> 外文期刊>Multimedia Tools and Applications >Smart motion reconstruction system for golf swing: a DBN model based transportable, non-intrusive and inexpensive golf swing capture and reconstruction system
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Smart motion reconstruction system for golf swing: a DBN model based transportable, non-intrusive and inexpensive golf swing capture and reconstruction system

机译：高尔夫挥杆动作的智能运动重构系统：基于DBN模型的可移动，非侵入式且廉价的高尔夫挥杆捕捉和重构系统

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摘要

In the past decade, golf has stimulated people's great interest and the number of golf players has increased significantly. Therefore, how to train a golfer to make a perfect swing has attracted extensive research attentions. Among these researches, the most important step is to capture and reconstruct the swing movement in a transportable and non-intrusive way. Restricted by the development of present depth imaging devices, the initial captured swing movement may not be acceptable due to occlusions and mixing up of body parts. In this paper, to restore motion information from self-occlusion and reconstruct 3D golf swing from low resolution data, a Dynamic Bayesian Network (DBN) model based golf swing reconstruction algorithm is proposed to increase the capture accuracy considering the spatial and temporal similarities of swing between different golfers. A Smart Motion Reconstruction system for Golf swing, SMRG, is presented based on the DBN model with a popular depth imaging device, Kinect, as capturing device. Experimental results have proved that the proposed system can achieve comparable reconstruction accuracy to the commercial optical motion caption (OMocap) system and better performance than state of art modification algorithms using depth information.
机译：在过去的十年中，高尔夫引起了人们的极大兴趣，高尔夫选手的数量大大增加了。因此，如何训练高尔夫球手进行完美的挥杆已经引起了广泛的研究关注。在这些研究中，最重要的步骤是以可移动且非侵入的方式捕获和重建挥杆动作。受当前深度成像设备的发展限制，由于闭塞和身体部位混合，最初捕获的挥杆动作可能是不可接受的。在本文中，为了从自闭塞中恢复运动信息并从低分辨率数据中重建3D高尔夫挥杆，提出了一种基于动态贝叶斯网络（DBN）模型的高尔夫挥杆重构算法，以考虑挥杆的时空相似性来提高捕获精度。在不同的高尔夫球手之间。基于DBN模型，提出了一种用于高尔夫挥杆的智能运动重构系统SMRG，该系统具有流行的深度成像设备Kinect作为捕获设备。实验结果证明，与使用深度信息的最新修改算法相比，该系统可实现与商用光学字幕（OMocap）系统相当的重建精度，并具有更好的性能。

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