How-To build 3D camera data using true colour information?

Combining 3D Depth Data with RGB Color for Advanced Robot Vision | 3D Vision Tutorial

In this video tutorial, we explore how to enhance 3D vision applications by combining spatial data from stereo vision cameras with true color information from RGB cameras. This fusion is essential for tasks like robotic sorting based on object color and shape. Learn how to accurately map RGB data to 3D point clouds and meshes to unlock the full potential of your robot vision system.

Session Timeline:

  • 01:43 – Visualizing 3D Data

  • 02:02 – Creating and Using PointClouds

  • 03:10 – 3D Mesh Generation

  • 04:20 – Mapping Color to 3D Data

  • 07:00 – Projecting to Color Images

  • 08:37 – RGB and 3D Camera Calibration

  • 09:10 – Using FileCamera in NxView

  • 10:00 – Exporting 3D Mesh Files

  • 10:23 – Viewing in CloudCompare

  • 11:33 – Mapping to Left Image of Ensenso

  • 13:34 – Storing Depth as Grayscale

  • 13:54 – Mapping to RGB Image

  • 14:49 – Summary

  • 16:05 – Advantages of Mapped 3D Data

Key Benefits:

  • Improved object detection and classification

  • Enhanced accuracy for robotics and automation

  • Seamless integration of color and depth data

Whether you're working in industrial automation, robotics, or 3D computer vision, this session will guide you through essential techniques to combine depth and color data effectively.

Watch now to learn how to map, and visualize RGB and 3D data for real-world robotics applications!

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Speaker Ute Seitz
Ute Seitz
Machine Vision Specialist

IDS Imaging Development Systems GmbH

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