Bedienungsanleitung

3D-EasyCalib™ 2.10.15

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User manual

Features

Intrinsic Camera Calibration

Estimation of intrinsic camera parameters from multiple images of a calibration target. The target recognition and the extraction of the calibration points with subpixel accuracy are carried out automatically.
Use cases: Lens distortion correction, 3D projection

Camera-Projector Calibration

Robust and accurate projector calibration with a complementary gray code sequence. This pattern can be generated for any projector resolution and robustly decoded in the camera image.
Use cases: 3D structured light imaging, augmented reality projection

Hand-Eye Calibration

Compute a rigid transformation between a camera mounted on the robot actuator and the actuator itself by a fixed calibration target in your environment.
Use cases: bin picking

Extrinsic Stereo Calibration

Determine the relative geometric orientation and position of two cameras to each other. Similar to intrinsic calibration, the targets and calibration points are recognized automatically. Intrinsic parameters can be computed during the extrinsic calibration process or input manually.
Use cases: depth sensing, 3D coordinate transformation, sensor fusion

Manhattan World Calibration

The orientation and position of a camera is determined using a Manhattan world assumption without the use of calibration targets.

Tool-Flange and Robot-World Calibration

Compute geometric transformations between stationary cameras and robot bases as well as robot-tools or -flanges with calibration targets on the robot.
Use cases: robot-assisted inspection control, machine-human collaboration

Base Module
  • Intrinsic Calibration
  • Stereo Calibration
  • Target Pose (PnP)
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Structured Light
  • Base Module
  • Intrinsic Projector-Calibration
  • Extrinsic Camera-Projector Calibration
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Robot Calib
  • Base Module
  • Hand-Eye Calibration
  • Tool-Flange / Robot-World
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Manhattan World
  • Base Module
  • Manhattan World Calibration
Send an Inquiry

Use cases

Intrinsic calibration of a KinectV2 IR camera. On the left side of the window is the list of calibration images. These are shown in color according to the size of the calibration error, from green (min error) to red (max error). In the middle is the image of a selected target pose with detected calibration points (circles) and the points computed according to the camera model (crosses). The color of the circles encodes the absolute difference between these points. The various target poses in the camera’s coordinate system are displayed on the right.
Intrinsic calibration of a KinectV2 IR camera. On the left side of the window is the list of calibration images. These are shown in color according to the size of the calibration error, from green (min error) to red (max error). In the middle is the image of a selected target pose with detected calibration points (circles) and the points computed according to the camera model (crosses). The color of the circles encodes the absolute difference between these points. The various target poses in the camera’s coordinate system are displayed on the right.
Extrinsic calibration of an imaging THz scanner (body scanner) and a monochrome camera for a depth-based sensor fusion. On the left is the image of the target taken with a standard camera and in the middle the image of the same target recorded with the THz camera. The 3D view on the right uses the camera coordinate systems to show the relative orientation and position of these two sensors to another as well as the different target poses.
Extrinsic calibration of an imaging THz scanner (body scanner) and a monochrome camera for a depth-based sensor fusion. On the left is the image of the target taken with a standard camera and in the middle the image of the same target recorded with the THz camera. The 3D view on the right uses the camera coordinate systems to show the relative orientation and position of these two sensors to another as well as the different target poses.
User interface for the robot/world and tool/flange calibration. The left column shows the individual camera recordings with color-coded reprojection errors. In the column next to it, the TCP poses are marked according to the 3D error. A selected image is shown in the center and the components are shown in 3D on the right.
User interface for the robot/world and tool/flange calibration. The left column shows the individual camera recordings with color-coded reprojection errors. In the column next to it, the TCP poses are marked according to the 3D error. A selected image is shown in the center and the components are shown in 3D on the right.
Demonstrator of a workstation for assembly processes at ZBS e. V. (left). The assembly worker’s actions are verified by tracking his hands with several cameras and comparing the information with an assembly process plan. The sensor system consists of a time-of-flight camera for person recognition, three active stereo cameras for component recognition and hand tracking, and a projector for augmentation. The illustration on the right shows the calibrated components of the assembly in the software front end of the 3D-EasyCalib™.
Demonstrator of a workstation for assembly processes at ZBS e. V. (left). The assembly worker’s actions are verified by tracking his hands with several cameras and comparing the information with an assembly process plan. The sensor system consists of a time-of-flight camera for person recognition, three active stereo cameras for component recognition and hand tracking, and a projector for augmentation. The illustration on the right shows the calibrated components of the assembly in the software front end of the 3D-EasyCalib™.
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Steb-by-Step Tutorials WITH 3D-EASYCalib

Intrinsic Camera Calibration

This introductory tutorial shows how to intrinsically calibrate a camera. You will learn how to specify target detection parameters correctly and how to identify and remove outliers to achieve optimal calibration results.

Camera-Projector Calibration

Learn how to calibrate a projector using a Gray code pattern. The tutorial also shows how to estimate extrinsic parameters of a camera and a projector.

Hand-Eye Calibration

In this tutorial, you will learn how to accurately estimate the rotation and translation of a camera mounted on a gripper with respect to the tool center point.

Extrinsic Stereo Calibration

A tutorial is coming soon ...

  • Sample Files
  • Tutorial

Manhattan World Calibration

A tutorial is coming soon ...

  • Sample Files
  • Tutorial

Tool-Flange and Robot-World Calibration

If you are observing a robot with a static camera and want to estimate the position and orientation of the robot base coordinate system in relation to the camera, then follow this tutorial.

Publications

Darko Vehar, Rico Nestler, Karl-Heinz Franke: “3D-EasyCalib™ – Toolkit zur geometrischen Kalibrierung von Kameras und Robotern” in 22. Anwendungsbezogener Workshop zur Erfassung, Modellierung, Verarbeitung und Auswertung von 3D-Daten “3D-NordOst”, GFaI Gesellschaft zur Förderung angewandter Informatik e.V. Berlin, S. 15 ff., ISBN: 978-3-942709-24-8, Dezember 2019.

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