Autonomous Driving

Label LiDAR and RADAR data for vehicle, pedestrian, and road sign detection.

360° Sensor Fusion

Synchronized 360° LiDAR point cloud projection with multi-camera fusion, tracking vehicles and pedestrians across dense traffic corridors.

Multi-View 3D Cuboids

Centimeter-accurate 3D bounding box annotation using synchronized top, front, and side orthographic projections with 6-DOF spatial rotation.

Semantic Street Segmentation

Point-level semantic classification of drivable road corridors, sidewalks, curbs, vehicles, and roadside infrastructure.

Camera-to-LiDAR Alignment

Multi-modal cross calibration between high-resolution optical video frames and raw LiDAR return pulses for robust autonomous perception.

Drone and Aerial Surveys

Annotate photogrammetry and aerial LiDAR for land use, infrastructure, and environmental analysis.

Aerial 3D Building Extraction

End-to-end aerial pipeline from RGB drone capture to dense white-point LiDAR, top-down projection, and volumetric 3D building bounding boxes.

Urban Planning

Label 3D data to model cityscapes and optimize infrastructure.

BIM & Structural Digital Twins

High-fidelity structural LiDAR scanning with edge and polygon boundary delineation for building information modeling (BIM) and smart cities.

Facility & Interior 3D Scanning

Comprehensive 5-stage interior spatial mapping: range imagery, point cloud intensity, semantic polygon wireframes, and 3D bounding boxes.

Warehouse Automation

Label RADAR and LiDAR for robot training and inventory management.

LiDAR AGV Perception Pipeline

End-to-end warehouse perception pipeline: original feed, range-ring LiDAR vision, depth range heatmap, semantic polygons, and 3D bounding boxes.

Multimodal Vision & Depth Grid

Multi-modal dataset coordination combining RGB optical footage, semantic class masks, and distance depth estimation for automated forklifts.

Defense and Security

Annotate 3D data for perimeter security, tactical situational awareness, and obstacle detection.

Tactical Perimeter & Base Surveillance

5-stage military defense LiDAR pipeline: original drone reconnaissance, height-colored point clouds, BEV elevation maps, semantic point segmentation, and 3D bounding box annotation.

Frequently Asked Questions

3D point cloud annotation operates in volumetric space — annotators must place 3D bounding boxes, draw polygon meshes, and classify individual points across XYZ coordinates and time dimensions. It requires specialized tooling, spatial reasoning skills, and domain expertise in LiDAR sensor physics that standard image annotators do not possess.

3D Point CloudAnnotation

Multi-Sensor Fusion & Dynamic LiDAR Tracking

Your spatial data problemhas a human solution.

Autonomous Driving

Digital Twins & Mapping

Robotics & Warehouse

Sensor Fusion Alignment

Our Annotation Services for 3D Point Cloud & LiDAR Data

Autonomous Driving — 360° Sensor Fusion

A Futureproofed 3D Pipeline

Data Intake

Annotation

QA

Delivery

Estimate Your Costs for ML projects

1 Pick application field

2 Select annotation method

3 Specify how many objects to label

4 Check the approximate total cost

5 Run free pilot

Why Projects Choose Engai for 3D Data Annotation

Accelerate Autonomy

Unmatched Precision

Infinite Scalability

Safe and secure

Start Free Piloting your ML project !

Live Infrastructure Telemetry

Zero-Trust Dataset Confidentiality

Frequently Asked Questions

What makes LiDAR point cloud annotation different from standard 2D annotation?

Which point cloud formats and sensor types does Engai support?

How do you ensure annotation accuracy in sparse or noisy point clouds?

3D Point Cloud
Annotation

Your spatial data problem
has a human solution.