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The Contribution of Stereoscopic and Motion Depth Cues to the Perception of Structures in 3D Point Clouds

机译:立体和运动深度提示对3D点云中结构感知的贡献

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摘要

Particle-based simulations are used across many science domains, and it is well known that stereoscopic viewing and kinetic depth enhance our ability to perceive the 3D structure of such data. But the relative advantages of stereo and kinetic depth have not been studied for point cloud data, although they have been studied for 3D networks. This article reports two experiments assessing human ability to perceive 3D structures in point clouds as a function of different viewing parameters. In the first study, the number of discrete views was varied to determine the extent to which smooth motion is needed. Also, half the trials had stereoscopic viewing and half had no stereo. The results showed kinetic depth to be more beneficial than stereo viewing in terms of accuracy and so long as the motion was smooth. The second experiment varied the amplitude of oscillatory motion from 0 to 16 degrees. The results showed an increase in detection rate with amplitude, with the best amplitudes being 4 degrees and greater. Overall, motion was shown to yield greater accuracy, but at the expense of longer response times in comparison with stereoscopic viewing.
机译:基于粒子的模拟已在许多科学领域中使用,众所周知,立体观察和动力学深度增强了我们感知此类数据的3D结构的能力。但是,尽管已经针对3D网络进行了研究,但尚未针对点云数据研究立体和动力学深度的相对优势。本文报告了两个实验,这些实验评估了人类感知点云中3D结构作为不同查看参数的函数的能力。在第一个研究中,改变了离散视图的数量来确定需要平滑运动的程度。而且,一半的试验具有立体观看效果,一半的试验没有立体效果。结果表明,只要运动平稳,动力学深度在准确性方面就比立体观看更有利。第二个实验将振荡运动的幅度从0度更改为16度。结果表明,检出率随振幅的增加而增加,最佳振幅为4度或更大。总体而言,运动显示出更高的准确性,但与立体观察相比,其响应时间更长。

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