Documentation
  • Introduction
  • Tutorials
    • Getting started
    • Python SDK quickstart
    • Model-assisted labeling
  • How to annotate
    • Label images
      • View and navigate in the image interfaces
      • Image interface settings
      • Image segmentation interface
      • Image vector interface
    • Label 3D point clouds
      • View and navigate in the 3D interface
      • Upload, view, and overlay images
      • 3D interface settings
      • 3D point cloud cuboid interface
      • 3D point cloud vector interface
      • 3D point cloud segmentation interface
      • Merged point cloud view (for static objects)
      • Batch mode (for dynamic objects)
      • Smart cuboid propagation
      • 3D to 2D Projection
      • Tips for labeling cuboid sequences
    • Label sequences of data
      • Use track IDs in sequences
      • Use keyframe interpolation
    • Annotate object links (beta)
    • Customize hotkeys
  • How to manage
    • Add collaborators to a dataset
    • Create an organization
    • Configure the label editor
    • Customize label queue
    • Search within a dataset
    • Clone a dataset
    • Work with issues
    • Bulk change label status
    • Manage QA processes
  • How to integrate
    • Import data
      • Cloud integrations
    • Export data
      • Structure of the release file
      • Exporting image annotations to different formats
    • Integrations
      • Hugging Face
      • W&B
      • Databricks
      • SceneBox
    • Create an API key
    • Upload model predictions
    • Set up webhooks
  • Background
    • Main concepts
    • Sequences
    • Label queue mechanics
    • Labeling metrics
    • 3D Tiles
    • Security
  • Reference
    • Python SDK
    • Task types
    • Sample formats
      • Supported file formats
    • Label formats
    • Categories and attributes
    • API
Powered by GitBook
On this page
  • Why use 3D tiles?
  • How to enable 3D tiles

Was this helpful?

  1. Background

3D Tiles

PreviousLabeling metricsNextSecurity

Last updated 2 years ago

Was this helpful?

3D point clouds are collections of points in 3D space. Depending on the type of sensor used, the number of points in one scan can vary greatly. As 3D sensors have evolved, the resolution of 3D scans has generally increased. Furthermore, robots and autonomous vehicles typically have multiple 3D sensors. The outputs of these sensors can then be combined into one large point cloud scan.

High-resolution scans with hundreds of thousands of points, or even millions of points, make it easy to detect objects, but come at a cost of increased file size and compute requirements. This can become a problem when trying to label the point clouds in a browser. Due to the large file size of the point clouds, loading the point cloud files can take a long time, especially when the file is being loaded by a workforce in a region far from your data center. Displaying hundreds of thousands of points in the browser can also be taxing for the GPU, and if there are too many points, the labeling interface can become unresponsive.

To solve these issues, we've introduced an option to split your point clouds into 3D tiles. When viewing the point cloud, the application only loads the tiles which should be visible, and only loads the tiles that are close in high resolution. Thus, the point cloud can load faster, and the GPU can comfortably render all points. This approach is similar to the way Google Earth works; when you are zoomed out, the application only loads a low-resolution image of a whole area. When you zoom in, smaller high-resolution tiles are loaded automatically.

Why use 3D tiles?

  • Upload and label point clouds with no limits on the point cloud size

  • Enable a when labeling sequences of point clouds

  • Enable the for labeling dynamic objects in point cloud sequences

How to enable 3D tiles

This feature is currently available behind a feature flag. if you'd like to enable 3D tiles for your point clouds.

3D tiles are currently only available for 3D vector labeling tasks (cuboid, polygon/polyline, and keypoint annotation). if you're interested in 3D tiles for point cloud segmentation.

merged point cloud view
batch mode
Contact us
Contact us