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

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.
Here, in order to determine the magnitude of velocity and acceleration for point...
Kinematic Equations for Rotation01:30

Kinematic Equations for Rotation

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...
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

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. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...

You might also read

Related Articles

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

Sort by
Same author

Magnetic character of the low-energy enhancement in <sup>70</sup>Zn.

Nature·2026
Same author

NeuroAIHub: An AI-Driven Framework for Automated Curation and Discovery of Neuroradiology Datasets.

AJNR. American journal of neuroradiology·2026
Same author

Association of CFRD development among females with CF who use hormonal contraception.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society·2026
Same author

Beta-Decay Half-Lives beyond ^{54}Ca: A Systematic Survey of Decay Properties Approaching the Neutron Dripline.

Physical review letters·2026
Same author

A phase II, randomized, open-label study to evaluate low-dose pembrolizumab plus chemotherapy versus chemotherapy as neoadjuvant therapy for localized triple-negative breast cancer (TNBC) (PLANeT trial-Pembrolizumab Low dose in Addition to NACT in TNBC).

Annals of oncology : official journal of the European Society for Medical Oncology·2025
Same author

Constraining the Synthesis of the Lightest p Nucleus ^{74}Se.

Physical review letters·2025

Related Experiment Video

Updated: May 29, 2026

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence
12:34

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence

Published on: June 24, 2016

Determining motion parameters for scenes with translation and rotation.

C Jerian1, R Jain

  • 1Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI 48109.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary

This study develops algorithms for camera rotation parameter estimation in computer vision. The hypothesize-and-verify method is proposed for improved motion parameter determination.

More Related Videos

Controlled Rotation of Human Observers in a Virtual Reality Environment
09:11

Controlled Rotation of Human Observers in a Virtual Reality Environment

Published on: April 21, 2022

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Related Experiment Videos

Last Updated: May 29, 2026

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence
12:34

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence

Published on: June 24, 2016

Controlled Rotation of Human Observers in a Virtual Reality Environment
09:11

Controlled Rotation of Human Observers in a Virtual Reality Environment

Published on: April 21, 2022

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Area of Science:

  • Computer Vision
  • Robotics
  • Image Processing

Background:

  • Estimating camera motion is crucial for tasks like 3D reconstruction and navigation.
  • Existing methods face challenges with real-world scene complexities.

Purpose of the Study:

  • To develop and evaluate methods for determining camera rotation parameters.
  • To compare hypothesize-and-verify approaches with relaxation labeling for motion estimation.

Main Methods:

  • Development of algorithms combining Jain and Prazdny's ideas.
  • Implementation of the hypothesize-and-verify paradigm for motion parameter estimation.
  • Testing with both synthetic and real-world scene data.

Main Results:

  • Successful determination of translational and rotational parameters using developed algorithms.
  • Demonstration of the effectiveness of hypothesized motion parameters over relaxation labeling for correspondence.
  • Identification of challenges in real scenes, including noise and resolution limitations.

Conclusions:

  • The hypothesize-and-verify approach offers a viable method for camera motion parameter estimation.
  • Further advancements in low-level vision techniques are needed for robust real-scene analysis.