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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

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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...
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Calibration Curves: Linear Least Squares01:20

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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.
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Glassware Calibration01:11

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Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
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Calibration Curves: Correlation Coefficient01:10

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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...
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Introduction and Methods of Leveling01:26

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Leveling is a surveying procedure used to determine elevation differences between distant points. Elevation refers to the vertical distance above or below a reference datum, typically mean sea level (MSL). In the United States, elevations are often referenced to the mean sea level station at Father Point Rimouski along the St. Lawrence Seaway. To make the datum accessible, permanent markers are established throughout the region. These markers, called benchmarks, have known elevations. If the...
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Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
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A Novel AVM Calibration Method Using Unaligned Square Calibration Boards.

Jung Hyun Lee1, Dong-Wook Lee1

  • 1Department of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea.

Sensors (Basel, Switzerland)
|April 3, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new around view monitoring (AVM) calibration method simplifying the process. The novel approach uses fewer, randomly placed calibration boards, reducing calibration time and effort for AVM systems.

Keywords:
around view monitoring systemautomatic camera calibrationvision-based advanced driver assistance systems

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Area of Science:

  • Computer Vision
  • Automotive Technology
  • Robotics

Background:

  • Around View Monitoring (AVM) systems enhance vehicle safety by providing a comprehensive view using multiple cameras.
  • Conventional AVM calibration relies on Maximum Likelihood Estimation (MLE), which necessitates extensive and precise placement of calibration boards.
  • The manual calibration process is labor-intensive and prone to inaccuracies, hindering widespread adoption and efficiency.

Purpose of the Study:

  • To develop a simplified and more efficient calibration method for Around View Monitoring (AVM) systems.
  • To reduce the complexity and manual effort involved in calibrating vehicle surround-view camera systems.
  • To enable accurate AVM image generation with minimal calibration resources.

Main Methods:

  • Proposed a novel AVM calibration technique that estimates the location of randomly placed calibration boards.
  • Defined Around View Monitoring (AVM) errors and identified parameters to minimize location estimation errors.
  • Validated the method's accuracy through experimental evaluations on different vehicle types.

Main Results:

  • The proposed method successfully calibrates AVM systems using only four randomly positioned calibration boards.
  • Experimental results demonstrate that the novel calibration method achieves accuracy comparable to conventional techniques.
  • The method's effectiveness is independent of vehicle size, as shown with a full-sized and a child's electric vehicle.

Conclusions:

  • The novel AVM calibration method significantly simplifies the calibration procedure, reducing effort and time.
  • This approach offers a practical and accurate solution for AVM system calibration across various vehicle platforms.
  • The method holds potential for improving the efficiency and accessibility of AVM technology in the automotive industry.