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Semantic Pointing for Object Picking in Complex 3D Environments

机译:复杂3D环境中对象拾取的语义指向

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Today's large and high-resolution displays coupled with powerful graphics hardware offer the potential for highly realistic 3D virtual environments, but also cause increased target acquisition difficulty for users interacting with these environments. We present an adaptation of semantic pointing to object picking in 3D environments. Essentially, semantic picking shrinks empty space and expands potential targets on the screen by dynamically adjusting the ratio between movement in visual space and motor space for relative input devices such as the mouse. Our implementation operates in the image-space using a hierarchical representation of the standard stencil buffer to allow for real-time calculation of the closest targets for all positions on the screen. An informal user study indicates that subjects perform more accurate pointing with semantic 3D pointing than without.
机译:当今的大型,高分辨率显示器以及功能强大的图形硬件为高度逼真的3D虚拟环境提供了潜力,但也给与这些环境进行交互的用户增加了目标获取难度。我们提出了一种针对3D环境中对象拾取的语义指向的改编。本质上,语义选择通过动态调整相对输入设备(例如鼠标)的视觉空间和运动空间之间的比例来缩小空白空间并扩大屏幕上的潜在目标。我们的实现使用标准模板缓冲区的分层表示在图像空间中进行操作,以便实时计算屏幕上所有位置的最接近目标。非正式的用户研究表明,使用语义3D指向的对象比没有使用语义3D指向的对象执行更准确的指向。

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