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Related Concept Videos

Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
Instrument Calibration01:12

Instrument Calibration

Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the other increases, and...
Distance Measurements by Taping01:18

Distance Measurements by Taping

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Related Experiment Video

Updated: May 26, 2026

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)
11:57

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)

Published on: December 1, 2016

Range camera self-calibration based on integrated bundle adjustment via joint setup with a 2D digital camera.

Mozhdeh Shahbazi1, Saeid Homayouni, Mohammad Saadatseresht

  • 1Department of Geomatics Engineering, University of Tehran, North Amriabad Street, Tehran 11155-4563, Iran. shahbazi.m@ut.ac.ir

Sensors (Basel, Switzerland)
|December 14, 2011
PubMed
Summary

This study introduces a new self-calibration method for time-of-flight cameras using a digital RGB camera. The integrated approach significantly improves range and coordinate accuracy by correcting systematic errors.

Keywords:
PMD range camerabundle adjustmentdigital cameraintegrated self-calibrationinternal errorjoint setuprange systematic error

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Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)
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Area of Science:

  • Photogrammetry
  • Computer Vision
  • Sensor Calibration

Background:

  • Time-of-flight (ToF) cameras, utilizing photonic mixer device (PMD) technology, offer high frame rate distance measurements.
  • Systematic errors in range and intensity data from PMD cameras necessitate correction for accurate 3D reconstruction.
  • Existing calibration methods for ToF cameras have limitations in field of view and resolution.

Purpose of the Study:

  • To present an integrated self-calibration method for PMD cameras using a joint setup with a digital RGB camera.
  • To simultaneously estimate systematic range error parameters and intrinsic/extrinsic camera orientation.
  • To enhance the accuracy and reliability of 3D data acquired by ToF cameras.

Main Methods:

  • A novel photogrammetric bundle adjustment approach is employed, integrating collinearity conditions and a range error model.
  • The calibration utilizes observation equations derived from both the PMD and digital RGB cameras.
  • A multi-resolution test field with high-contrast targets was used for data acquisition with a PMD[vision]-O3 camera.

Main Results:

  • The proposed integrated calibration method demonstrated an 83% improvement in Root Mean Square (RMS) range error and a 72% improvement in RMS coordinate residual compared to basic calibration.
  • Significant accuracy enhancements were observed over single PMD camera integrated calibration, with 25% and 36% improvements in RMS range error and coordinate residual, respectively.
  • The joint setup effectively overcomes the limitations of small field of view and low pixel resolution inherent in standalone PMD cameras.

Conclusions:

  • The integrated self-calibration method offers a robust solution for correcting systematic errors in PMD cameras.
  • Combining PMD and digital cameras in a joint calibration framework significantly boosts 3D measurement accuracy.
  • This approach provides a more reliable and precise method for applications requiring accurate depth information from ToF sensors.