The invention of depth sensors for mobile devices, has led to availability of relatively inexpensive high-resolution depth and visual (RGB) sensing for a wide range of applications. The complementary nature of the depth and visual information opens up new opportunities to solve fundamental problems in object and activity recognition, people tracking, 3D mapping and localization, etc. One of the most interesting challenges that can be tackled by using these sensors is tracking the body movements of athletes and providing natural interaction as a result. In this study depth sensors and gesture recognition tools will be used to analyze the position and angle of an athlete’s body parts thought out an exercise. The goal is to assess the training performance of an athlete and decrease injury risk by giving warnings when the trainer is performing a high risk activity.

中文翻译：

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基于手势的人机交互，用于运动训练

用于移动设备的深度传感器的发明已经导致相对便宜的高分辨率深度和视觉（RGB）感测可用于广泛的应用。深度和视觉信息的互补性质为解决对象和活动识别，人员跟踪，3D映射和本地化等基本问题提供了新的机会。使用这些传感器可以解决的最有趣的挑战之一是跟踪运动员的身体运动，从而提供自然的互动。在这项研究中，深度传感器和手势识别工具将用于分析锻炼后运动员身体部位的位置和角度。