Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

519
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
519
Kinematic Equations for Rotation01:30

Kinematic Equations for Rotation

354
In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
For instance, imagine a point A on a rigid body engaged in circular motion. The translational velocity of this particular point can be calculated by taking the time derivatives of the displacement equation, which essentially measures the...
354
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

505
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
505
Curvilinear Motion: Normal and Tangential Components01:27

Curvilinear Motion: Normal and Tangential Components

429
When a car traverses a curved road, its motion can be elucidated by breaking it down into tangential and normal components. The car-centric coordinates attached to the vehicle move with it.
The positive direction of the t-axis aligns with the increasing position of the car along the curved path, denoted by the unit vector ut. Simultaneously, the n-axis, perpendicular to the t-axis, dissects the curved path into differential arc segments, each forming the arc of a circle with a radius of...
429
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

425
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.
Here, in order to determine the magnitude of velocity and acceleration for point...
425
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

490
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...
490

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Does Leisure-Time Physical Activity Buffer the Negative Impact of Alcohol Use on Loneliness in Older Adults?

International journal of aging & human development·2026
Same author

Machine-learning-guided inverse design of lead-free relaxors enabled by multimodal literature mining.

Nature communications·2026
Same author

Temporal trends in treatment-requiring microvascular complications in young-onset diabetes: A nationwide population-based study.

Diabetes research and clinical practice·2026
Same author

Development and effectiveness of a mindfulness-based cognitive therapy for individuals with spinal cord injury: Changes in quality of life and inflammatory biomarkers.

The journal of spinal cord medicine·2026
Same author

Corrigendum to "Temporal trends in macrovascular complications in young-onset diabetes in Korea: A nationwide population-based study" [Diabetes Res. Clin. Pract. 236 (2026) 113285].

Diabetes research and clinical practice·2026
Same author

Core Microbiota Drives Host-Specific Growth Enhancement: Evidence in a Harmful Algal Bloom Causing Dinoflagellate <i>Prorocentrum lima</i>.

Environmental science & technology·2026

Related Experiment Video

Updated: Jul 27, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.1K

Noniterative Generalized Camera Model for Near-Central Camera System.

Taehyeon Choi1, Seongwook Yoon1, Jaehyun Kim1

  • 1School of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.

Sensors (Basel, Switzerland)
|June 10, 2023
PubMed
Summary

This study introduces a new camera calibration method for non-central cameras, improving accuracy and speed. The approach uses sparse points and a smoothed 3D residual framework for efficient and precise camera model calibration.

Keywords:
3D measurecamera calibrationcatadioptric camera modelfisheye camera modelgeneralized camera modelrefraction of ray near-central camera modelstereo camera calibrationtransparent shield

More Related Videos

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K
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

10.8K

Related Experiment Videos

Last Updated: Jul 27, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.1K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K
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

10.8K

Area of Science:

  • Computer Vision
  • Geometric Modeling

Background:

  • Conventional camera calibration methods struggle with non-central camera models.
  • Generalized camera models require dense points and are computationally intensive.

Purpose of the Study:

  • To develop an efficient and accurate calibration method for near-central cameras.
  • To address limitations of existing iterative and dense-point dependent calibration techniques.

Main Methods:

  • Proposed a non-iterative ray correction method using sparse observation points.
  • Established a smoothed three-dimensional (3D) residual framework.
  • Utilized local inverse distance weighting for residual interpolation.

Main Results:

  • Achieved prompt and accurate camera calibration.
  • Reduced depth error by approximately 63% on the bumpy shield dataset.
  • Demonstrated a speed improvement of two orders of magnitude over iterative methods.

Conclusions:

  • The proposed non-iterative method offers a computationally efficient and accurate solution for near-central camera calibration.
  • Smoothed 3D residual vectors provide more accurate ray direction representation than 2D entities.