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Joint Filtering: Enhancing gesture and mouse movement in Microsoft Kinect application

机译:联合过滤:在Microsoft Kinect应用程序中增强手势和鼠标移动

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One of the most imperative research areas in the field of Human Computer Interaction (HCI) is gesture recognition as it provides a natural and spontaneous way to communicate between people and machines. Gesture based applications range from computer games to virtual augmented reality and is recently being explored in other fields. The idea behind this work is to attempt to tackle the problem of gesture movement of the human body using Microsoft Kinect sensor. The skeletal tracking (ST) system of the Natural User Interface (NUI) provides joint positions of tracked persons skeletons. These joint positions are the data consumed as position and pose, and they are used for many purposes, such as gesture detection, navigating user interfaces, and so on. The filter method used is Holt exponential smoothing filter. This filter smooth out the jitter, adds the capability to continue tracking for a short period of time when the subject moves out of range of the sensor, and improves the accuracy of the tracking by incorporating the information.
机译:手势识别是人机交互(HCI)领域中最重要的研究领域之一,因为它提供了一种自然而自发的人与机器之间进行通信的方式。基于手势的应用程序范围从计算机游戏到虚拟增强现实,最近在其他领域也正在探索中。这项工作背后的想法是尝试使用Microsoft Kinect传感器解决人体的手势移动问题。自然用户界面(NUI)的骨骼跟踪(ST)系统提供了被跟踪人员骨骼的联合位置。这些关节位置是作为位置和姿势消耗的数据,它们用于许多目的,例如手势检测,导航用户界面等。所使用的滤波方法是Holt指数平滑滤波。该滤镜可以消除抖动,增加当对象移出传感器范围时可以在短时间内继续跟踪的功能,并通过合并信息来提高跟踪的准确性。

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