Autonomous Vehicle Data Labeling

Data labeling strategies for self-driving car datasets including LiDAR point clouds, camera images, radar, and multi-sensor fusion annotation.

Autonomous Vehicle Data Types

• Camera Images - 2D object detection, lane detection, traffic sign recognition, semantic segmentation
• LiDAR Point Clouds - 3D bounding boxes, point-wise semantic segmentation, object tracking
• Radar Data - Object detection and velocity estimation
• Sensor Fusion - Combined annotations projecting 3D labels onto 2D camera views

Autonomous Vehicle Labeling Challenges

• Massive data volumes (terabytes of sensor data per day)
• Complex temporal tracking across sequential frames
• Long-tail distribution of rare but critical scenarios (edge cases)
• Precise calibration between sensors for fusion
• Safety-critical accuracy requirements for ADAS