Skeletonization using thinning method for human motion system

Wahyu Andhyka Kusuma, Lailatul Husniah
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引用次数: 3

Abstract

Natural interaction is a form of human interaction with computers that shows human behavior towards computers. Kinematic presents the synthesis of three-dimensional computer graphics (3D) into the real world. Microsoft Kinect 3D sensor can help develop research in the field of kinematics by using RGB and depth images that can be used to improve the results of previous studies. Problems encountered in detecting kinematic is to determine the point features that will be used. The problems that exist in previous studies can be reduced by using the depth image generated by the Kinect. Depth image produces a simple shape that is used to simplify and accelerate the detection skeleton that can be used as features in the kinematic. Our method combines the advantages of the two methods, dilatation and star skeleton. Experiments show that our method efficiently and fast to extract the skeleton of a depth image that can be used as the kinematic features.
基于细化方法的人体运动系统骨架化
自然交互是人类与计算机交互的一种形式,它显示了人类对计算机的行为。运动学展示了三维计算机图形学(3D)与现实世界的综合。微软Kinect 3D传感器可以通过使用RGB和深度图像来帮助发展运动学领域的研究,可以用来改进以前的研究结果。在运动学检测中遇到的问题是确定将要使用的点特征。利用Kinect产生的深度图像可以减少以往研究中存在的问题。深度图像产生一个简单的形状,用于简化和加速检测骨架,可以用作运动学特征。我们的方法结合了膨胀法和星骨架法两种方法的优点。实验结果表明,该方法能够有效、快速地提取深度图像的骨架作为图像的运动特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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