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A POINT-BASED VIRTUAL REALITY SYSTEM FOR SUPPORTING PRODUCT DEVELOPMENT

机译：用于支持产品开发的基于点的虚拟现实系统

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摘要

In this paper, we discuss methods to efficiently render stereoscopic scenes of large-scale point-clouds on inexpensive VR systems. Recently, terrestrial laser scanners are significantly improved, and they can easily capture tens of millions points in a short time from large fields, such as engineering plants. If 3D stereoscopic scenes of large-scale point-clouds could be easily rendered using inexpensive devices, they might be involved in casual product development phases. However, it is difficult to render a huge number of points using common PCs, because VR systems require high frame rates to avoid VR sickness. To solve this problem, we introduce an efficient culling method for large-scale point-clouds. In our method, we project all points onto angle-space panoramic images, whose axes are the azimuth and elevation angles of head directions. Then we eliminate occluded and redundant points according to the resolutions of devices. Once visible points are selected, they can be rendered in high frame rates. Visible points are updated when the user stays at a certain position to observe target objects. Since points are processed on image space in our method, preprocessing is very fast. In our experiments, our method could render stereoscopic views of large-scale point-clouds in high frame rates.
机译：在本文中，我们讨论了有效地在廉价VR系统上有效地呈现大规模点云的立体场景。最近，陆地激光扫描仪显着改善，它们可以在短时间内容易地从大型领域捕获数千万点，例如工程厂。如果使用廉价的设备可以轻松呈现大型点云的3D立体场景，则可能涉及随意的产品开发阶段。然而，很难使用公共P​​C渲染大量点，因为VR系统需要高帧速率以避免VR疾病。为了解决这个问题，我们介绍了大型点云的高效剔除方法。在我们的方法中，我们将所有点投射到角度空间全景图像上，其轴是顶部方向的方位角和高度角度。然后我们根据设备的分辨率消除封闭和冗余点。一旦选择了可见点，它们可以以高帧速率呈现。当用户留在某个位置以观察目标对象时，更新可见点。由于我们的方法中的图像空间处理点，因此预处理非常快。在我们的实验中，我们的方法可以在高帧速率下呈现大型点云的立体视图。

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