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3-D Cuboid annotation for Lidar

Drawing 3-D bounding boxes to annotate and/or measure many points on an external surface of an object. These typically are generated using 3-D laser scanners, RADAR sensors, and LiDAR sensors.

These are used to detect and monitor objects with greater precision, including single points, to gather information such as scale, position, speed, yaw, pitch, and class.

Point Cloud Segmentation

LiDAR point cloud segmentation is a technique for classifying an object with additional attributes that can be detected by any perception model for learning. 3D point cloud annotation services help self-driving cars differentiate between various types of lanes in a 3D point cloud map so that they can annotate the roads for safer driving with more accurate visibility using 3D orientation.

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How It Work's

Our Working Process

Get training data for you AI

01

Consultation

Our experts define strategic business objectives and outcomes of the project

02

Data Collection

Data is collected using various technologies with inhouse expertise as per requirement

03

Training & Data Annotation

The team is trained & annotations are performed to extract meaningful insights for training AI

04

Evaluation & Feedback

The data goes through stringent quality checks and sent for final deployment to meet the threshold accuracy

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Get Started

Get started with your project today

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