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  • 2D structure of the point cloud.[1]
  • Today, the “brain” is an expert behind a desk that will process the point cloud to extract deliverables.[2]
  • Moreover, the procedures to convert point clouds in application-specific deliverables are very costly in time/manual intervention.[2]
  • So yes, point clouds are huge; yes we need specific “tricks” to store them and process them, but so were videos back some decades ago ![2]
  • Pointly relies on state-of-the-art visualization engines that are capable of displaying point clouds with up to billions of points.[3]
  • G-PCC addresses the compression of point clouds in both Category 1 (static point clouds) and Category 3 (dynamically acquired point clouds).[4]
  • Build a unique spatio-temporal model of reality with 4D point clouds, combining 3D point clouds captured at different points in time.[5]
  • Point clouds can also be used to represent volumetric data, as is sometimes done in medical imaging.[6]
  • The system can be configured to provide both 3D point clouds as well as radial velocity and reflectivity data for each point.[7]
  • Point clouds are datasets that represent objects or space.[8]
  • Point clouds are a means of collating a large number of single spatial measurements into a dataset that can then represent a whole.[8]
  • Point clouds are most commonly generated using 3D laser scanners and LiDAR (light detection and ranging) technology and techniques.[8]
  • Point clouds are relatively easy to edit, display and to filter, and free software exists to do so.[8]
  • This question can pose a problem for some surveyors — and others may not know how to create a point cloud to begin with.[9]
  • How do you create a point cloud when it involves so much detail and so many small points?[9]
  • Site surveyors can create 3D models from point clouds by using LIDAR lasers.[9]
  • Once you have the complete point cloud, you can import it into a point cloud modeling software solution.[9]
  • A point cloud is a collection of data points defined by a given coordinates system.[10]
  • In a 3D coordinates system, for example, a point cloud may define the shape of some real or created physical system.[10]
  • Point clouds are collections of 3D points located randomly in space.[11]
  • The point cloud can be used directly, or converted to a 2.5D grid, a DTM or DSM.[11]
  • This shows a 3D depiction of the point cloud.[11]
  • This shows a slice through the point cloud.[11]
  • Point clouds are used to measure real-world scenes and are commonly produced by lidar scanners and other devices.[12]
  • When gathering as-built data from the existing structures, the output is often a 3D point cloud.[13]
  • A point cloud is often converted as 3D elements because of the size of a point cloud file.[13]
  • Some details and information are lost in modelling the point cloud, as a surface model approximates the information.[13]
  • One step of the workflow, the modelling, can be skipped in many occasions by using point clouds as BIM.[13]
  • A point cloud is nothing more than a collection of millions (sometimes billions) of points coming from a scanner.[14]
  • This type of scanner creates a point cloud by emitting a laser beam in a certain direction (described by angles φ and θ).[14]
  • Sweeping this beam around and measuring the distances to all these reflections on surfaces results in a point cloud (Figure 1 b and c).[14]
  • Point clouds only contain information on the outside of objects.[14]
  • The resulting point clouds (datasets) collected from these various technologies and platforms can be combined into one seamless 3D model.[15]
  • Point clouds are a major leap for our society transitioning many services from the real world to the virtual world.[15]
  • Sampling can be used to reduce the size of point clouds by eliminating points in over-sampled regions.[16]
  • Polygonica can create a mesh from all or part of a point cloud, in other words, Polygonica can do meshing.[16]
  • The tools provided by Polygonica are extremely flexible, can be applied to all or part of a point cloud, and in almost any sequence.[16]
  • Next, import the point cloud the scanner creates (and that you don’t initially see) into point-cloud modeling software.[17]
  • The software lets you visualize and model the point cloud, which at that stage looks rather like a pixelated, digital version of your site.[17]
  • In the same way, a point cloud is a huge number of tiny data points that exist in three dimensions.[17]
  • So the point cloud that the laser scanner captures is an accurate as-built of an object or space.[17]
  • Point locations are in the world coordinate space, consistent with the camera position for the frame that provided the point cloud.[18]
  • Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks.[19]
  • Segment based place recognition in 3D point clouds.[19]
  • Using 2 point+normal sets for fast registration of point clouds with small overlap.[19]
  • Real-time 3D Object Detection from Point Clouds.[19]
  • An ordered point cloud has only to do with the data being sorted in a particular sequence and is independent of the file type or format.[20]
  • Kaarta point clouds and all point clouds generated through continuous motion are unordered.[20]
  • Interoperability is another key to utilizing your modeled point cloud.[21]
  • A Point Cloud is a 3D visualization made up of thousands or even millions of georeferenced points.[22]
  • You can view 3D models as point clouds.[22]
  • The point cloud is 4x as dense, and data in overhanging regions is preserved.[22]
  • Select Point Cloud as Layer.[22]

소스

  1. ↑ msgs/PointCloud2 Documentation
  2. ↑ 2.0 2.1 2.2 The Future of 3D Point Clouds: a new perspective
  3. ↑ 3D point cloud classification made smart, fast and easy
  4. ↑ Geometry-based Point Cloud Compression
  5. ↑ Point Cloud Technology Home Page • Point Cloud Technology GmbH
  6. ↑ Point cloud
  7. ↑ pointcloud
  8. ↑ 8.0 8.1 8.2 8.3 What are point clouds? 5 easy facts that explain point clouds
  9. ↑ 9.0 9.1 9.2 9.3 What is Point Cloud Modeling?
  10. ↑ 10.0 10.1 Definition from WhatIs.com
  11. ↑ 11.0 11.1 11.2 11.3 Point Cloud Data
  12. ↑ Point Cloud
  13. ↑ 13.0 13.1 13.2 13.3 What is the Difference Between a Point Cloud and a 3D Model?
  14. ↑ 14.0 14.1 14.2 14.3 1: What's the point?
  15. ↑ 15.0 15.1 What Are Point Clouds? What are they used for? SurvTech Solutions
  16. ↑ 16.0 16.1 16.2 Point Clouds
  17. ↑ 17.0 17.1 17.2 17.3 What Is a Point Cloud?
  18. ↑ Google Developers
  19. ↑ 19.0 19.1 19.2 19.3 Yochengliu/awesome-point-cloud-analysis: A list of papers and datasets about point cloud analysis (processing)
  20. ↑ 20.0 20.1 Point Cloud Formats
  21. ↑ Point Cloud to CAD
  22. ↑ 22.0 22.1 22.2 22.3 3D Point Clouds

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