Paul Tice has been in the 3D scanning field for 20 years. The expert predicts that the development of 3D scanning will one day make 3D modeling history.
Tice is the executive director of ToPa 3D, a 3D visualization and design company. A few days ago, Xiao Bian found that he published an article related to point cloud data used by the Australian technology company Euclideon on LinkedIn, and caused a lot of discussion in the industry.
Point cloud problem
The point cloud is data collected by 3D scanning hardware, such as FARO's Focus 3D laser scanner and Shining 3D's Einscan Pro. The basic principle of capturing a 3D object is a single point when the 3D scanner feeds back the beam to the surface. Even if you scan the smallest object, the system will create millions of such points, so it is not easy to manage such massive data. CAD software can connect all points, but this process requires a lot of computing resources, and perfecting the finished product model is often a difficult process.
From point cloud (right) to finished 3D model (left and center)
Ulead's infinite detail algorithm is integrated into the SOLIDSCAN software to render the point cloud in real time for interactive 3D visualization of the scan. The company said, "This algorithm only grabs one point in each screen pixel, not every small dot."
When citing superior technology, Tice's following statement caused the industry's discussion:
If Unisys can animate a point cloud like a video presentation, it should be possible to allocate metadata for each point, where the data can be hosted as an IP in the Internet of Things. If this is possible, ToPa believes that one day, component and grid modeling will be eliminated because future smart models will consist of pure point cloud data. â€
Tice here predicts two potential directions for the "point cloud future": collecting metadata together with point clouds; a grid-independent smart 3D model.
2. In the Internet of Things
To solve the first meaning, feeding metadata to the smart IoT system can help the machine better respond to certain conditions. Information such as location, color, texture, scale, and how a point relates to other points can provide help for advancements in areas such as augmented reality, virtual reality, and the like.
When HTC Vive went public, VR became a hot topic for many technology companies. To prove that VR exists in real-world applications other than gaming, Dassault Systèmes, the 3D software giant, integrated HTC Vive into its 3DEXPERIENCE product viewer, enabling users to immerse in 3D designs.
As for the "intelligent 3D model independent of the grid", this will enable faster and more reliable 3D visual access. You Li cited 3D Google Earth type pictures as a future development of such a:
Imagine a 3D landscape that is large enough to extend to the horizon, but you can zoom in on a particle scattered on the ground in less than a second.
We don't know what you think, but we absolutely hope that we can make digital walks on the moon. Tice's point of view also drew attention:
Imagine using LiDAR to investigate the entire planet and observe it in real time.
This is definitely an exciting prospect for players. Merging sparse point cloud data into surfaces rather than polygons can provide a more realistic virtual world and reduce the load on host computing.
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