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Game Based Approach to Learn Martial Arts for Beginners

机译:基于游戏的方法,为初学者学习武术

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Long hours of training are required to achieve perfect motion in certain sports such as martial arts and dance. In this paper, we are trying to develop a game-based learning system for martial arts that required emphasis of gesture movement with the aid of Kinect sensor. Emergence of controller-less sensors in gaming industry was said to exhibit the potential of bringing joy and fun into teaching and learning experience. We had seen many commercialized controller-less sensors that enhanced the game experience, brought us one step closer to the virtual reality. No doubts, games have unique opportunity to create experiences that unfold over long span of time. Why not we have them kill two birds with one stone? Besides the pleasure brought by the game, we can have the player indirectly learn the real sport through the game play and subsequently train them within the long span of time during game play. Our main idea is to unobtrusively teach player about martial arts during the game play. We have chosen Kinect sensor for its affordability and ease of programming. We have evaluated accuracy of Kinect sensor for motions capture by developing a simple program in Xcode with OpenNI framework and NITE middleware to estimate the player's height by retrieving joint points coordinates information. We have obtained the results of 100% user detection rate, high accuracy but low precision for height estimation with Kinect. This analysis convinced that Kinect is suitable to replace wearable sensor and to fit in our system with proper adjustment and arrangement.
机译:在某些运动中,如武术和舞蹈,需要长时间的训练才能获得完美的运动。在本文中,我们正在尝试开发一种基于游戏的武术学习系统,该系统需要借助Kinect传感器来强调手势运动。据说游戏行业中无控制器传感器的出现展现了将欢乐和乐趣带入教学经验的潜力。我们已经看到了许多商业化的无控制器传感器,它们增强了游戏体验,使我们更接近于虚拟现实。毫无疑问,游戏拥有独特的机会来创造可以长时间延续的体验。我们为什么不让它们用一块石头杀死两只鸟?除了游戏带来的乐趣外,我们还可以让玩家通过玩游戏间接学习真实的运动,然后在玩游戏的很长一段时间内对其进行训练。我们的主要想法是在游戏过程中不打扰地向玩家传授武术。我们选择Kinect传感器是因为其价格适中且易于编程。我们通过使用OpenNI框架和NITE中间件在Xcode中开发一个简单程序,通过检索关节点坐标信息来估计玩家的身高,来评估Kinect传感器用于运动捕捉的准确性。通过Kinect进行高度估计,我们获得了100%用户检测率,高精度但低精度的结果。该分析表明,Kinect适用于替换可穿戴传感器,并通过适当的调整和布置适合于我们的系统。

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