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Metaphoric Hand Gestures for Orientation-Aware VR Object Manipulation With an Egocentric Viewpoint

机译:具有自我中心观点的定向感知VR对象操纵的隐喻手势

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摘要

We present a novel natural user interface framework, called Meta-Gesture, for selecting and manipulating rotatable virtual reality (VR) objects in egocentric viewpoint. Meta-Gesture uses the gestures of holding and manipulating the tools of daily use. Specifically, the holding gesture is used to summon a virtual object into the palm, and the manipulating gesture to trigger the function of the summoned virtual tool. Our contributions are broadly threefold: 1) Meta-Gesture is the first to perform bare hand-gesture-based orientation-aware selection and manipulation of very small (nail-sized) VR objects, which has become possible by combining a stable 3-D palm pose estimator (publicly available) with the proposed static-dynamic (SD) gesture estimator; 2) the proposed novel SD random forest, as an SD gesture estimator can classify a 3-D static gesture and its action status hierarchically, in a single classifier; and 3) our novel voxel coding scheme, called layered shape pattern, which is configured by calculating the fill rate of point clouds (raw source of data) in each voxel on the top of the palm pose estimation, allows for dispensing with the need for preceding hand skeletal tracking or joint classification while defining a gesture. Experimental results show that the proposed method can deliver promising performance, even under frequent occlusions, during orientation-aware selection and manipulation of objects in VR space by wearing head-mounted display with an attached egocentric-depth camera (see the supplementary video available at: http://ieeexplore.ieee.org).
机译:我们提出了一种新颖的自然用户界面框架,称为Meta-Gesture,用于在以自我为中心的观点中选择和操纵可旋转虚拟现实(VR)对象。 Meta-Gesture使用握住和操纵日常使用工具的手势。具体而言,握持手势用于将虚拟对象召唤到手掌中,而操纵手势用于触发被召唤的虚拟工具的功能。我们的贡献主要包括三方面:1)Meta-Gesture率先对裸露的小(指甲大小)VR对象执行基于手势的裸露姿势识别选择和操作,这通过结合稳定的3D图像已成为可能带有建议的静态(SD)手势估计器的手掌姿势估计器(可公开获得); 2)提出的新颖的SD随机森林,因为SD手势估计器可以在单个分类器中对3-D静态手势及其动作状态进行分层分类;和3)我们新颖的体素编码方案(称为分层形状图案)是通过计算手掌姿势估计顶部每个体素中点云(数据的原始数据)的填充率而配置的,从而无需定义手势时先进行手部骨骼跟踪或关节分类。实验结果表明,该方法通过佩戴头戴式显示器和一个以自我为中心的深度摄像头,可以在VR空间中的定向感知选择和操纵对象期间,即使在频繁遮挡的情况下,也可以提供有希望的性能(请参见位于以下位置的补充视频: http://ieeexplore.ieee.org)。

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