LiDAR Annotation in Data Annotation and Labeling Services

Importance for Autonomous Vehicles

• LiDAR Annotation: Critical for autonomous vehicles.
• Purpose: Identifies objects in a 3D point cloud.
• Process: Draws bounding cuboids around specified objects, providing positions and sizes.
• 3D Representation: Appears on a flat screen.
• Challenge: Managing a vast number of points not bounded by objects.

Benefits for Machine Learning

• Better Training: Enhances ML algorithms.
• Efficiency: Makes semantic and instance segmentation of long LiDAR data sequences highly efficient and accurate.
• Results: Allows for the segmentation of long sequences quickly with exceptional accuracy.

Integration with Machine Learning

• Technology: LiDAR annotation paired with machine learning delivers efficient and accurate outcomes.

Services by Learning Spiral

• Company: Learning Spiral specializes in data labeling services.
• Capabilities:
  • Drawing bounding boxes and cuboids
  • Polygon annotation
  • Picture classification
  • Tagging
  • Text annotation
  • Image masking annotation
  • Data annotation and labeling
  • 2D and 3D annotation
  • Semantic segmentation
  • 3D LiDAR annotation
  • Autonomous vehicle tagging
  • Aerial view picture tagging (drones)
  • Contour annotation