University of Central Florida, USA.
IEEE Trans Vis Comput Graph. 2012 Apr;18(4):634-42. doi: 10.1109/TVCG.2012.40.
3D object selection is more demanding when, 1) objects densly surround the target object, 2) the target object is significantly occluded, and 3) when the target object is dynamically changing location. Most 3D selection techniques and guidelines were developed and tested on static or mostly sparse environments. In contrast, games tend to incorporate densly packed and dynamic objects as part of their typical interaction. With the increasing popularity of 3D selection in games using hand gestures or motion controllers, our current understanding of 3D selection needs revision. We present a study that compared four different selection techniques under five different scenarios based on varying object density and motion dynamics. We utilized two existing techniques, Raycasting and SQUAD, and developed two variations of them, Zoom and Expand, using iterative design. Our results indicate that while Raycasting and SQUAD both have weaknesses in terms of speed and accuracy in dense and dynamic environments, by making small modifications to them (i.e., flavoring), we can achieve significant performance increases.
3D 对象选择在以下情况下要求更高：1）对象密集环绕目标对象，2）目标对象被显著遮挡，以及 3）当目标对象动态变化位置时。大多数 3D 选择技术和指南是在静态或稀疏环境中开发和测试的。相比之下，游戏往往将密集和动态的对象作为其典型交互的一部分。随着使用手势或运动控制器的游戏中 3D 选择的日益普及，我们对 3D 选择的现有理解需要修订。我们进行了一项研究，根据不同的对象密度和运动动态，在五种不同场景下比较了四种不同的选择技术。我们利用了两种现有的技术，射线投射和 SQUAD，并通过迭代设计开发了它们的两种变体，缩放和扩展。我们的结果表明，虽然射线投射和 SQUAD 在密集和动态环境中的速度和准确性方面都存在弱点，但通过对它们进行小的修改（即调味），我们可以显著提高性能。
