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3D Point Cloud Data Annotation Case Study

LiDAR Annotation

ByteBridge Point Cloud Annotation
ByteBridge Point Cloud Semantic Segmentation Annotation

Basic Information of Project

1. Annotation Categories

  • For people riding bikes, people and bikes should be labeled separately with two mutually overlapping boxes.
  • For people on vehicles, such as standing on a truck, people and vehicles should be labeled one by one.
  • Label vehicles with the number of the point cloud no less than five
  • Non-vehicles and pedestrians with point clouds no less than three
  • Vehicle parameters should be within the standard size and not allowed to exceed or be less than the standard parameters (except for obstacles with complete point cloud).
  • The size error range for the same obstacle in 2 continuous frames: length of 0.5m, width of 0.15m, and height of 0.15m; the parameter values of the obstacle should remain the same.
  • The size of the object is allowed to increase (the data before and after should be within the length of 0.5m, width of 0.15m, and height of 0.15m) in the first two and three frames, but the parameters after should tend to be steady).

You Configure and ByteBridge Annotates MANUALLY

Output

ByteBridge 3D Point Cloud Data Annotation
ByteBridge 3D Point Cloud Data JSON Output

End

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ByteBridge

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