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

505
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...
505
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

256
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
256
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

437
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...
437
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

505
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...
505
Deformation of Member under Multiple Loadings01:11

Deformation of Member under Multiple Loadings

203
When a rod is made of different materials or has various cross-sections, it must be divided into parts that meet the necessary conditions for determining the deformation. These parts are each characterized by their internal force, cross-sectional area, length, and modulus of elasticity. These parameters are then used to compute the deformation of the entire rod.
In the case of a member with a variable cross-section, the strain is not constant but depends on the position. The deformation of an...
203
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

401
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...
401

You might also read

Related Articles

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

Sort by
Same author

Entropy-stabilized quinary sulfide nanozyme for complementary dual-mode detection of sulfonamide antibiotics via electrochemiluminescence and colorimetric sensing.

Biosensors & bioelectronics·2026
Same author

Nutritional risk and cancer pain as determinants of radiotherapy-induced severe lymphocytopenia: development and validation of a nutrition-integrated predictive nomogram.

Frontiers in nutrition·2026
Same author

UBE2M-mediated neddylation modification stabilizes VEGFR2 to delay pulmonary vascular endothelial cell senescence.

Cell death & disease·2026
Same author

Oxidized lipids as molecular biomarkers in carotid in-stent restenosis: mechanisms and clinical implications.

Frontiers in neurology·2026
Same author

Comment on Rapid Whole genome sequencing of Plasmodium DNA from cryptic malaria cases in UK travellers provides insights into infection origins, transmission, and antimalarial resistance.

Journal of travel medicine·2026
Same author

Dual-targeted liposomes delivering ginsenoside CK attenuate cerebral ischemia-reperfusion injury by suppressing PANoptosis via O-GlcNAcylation of RIPK1/RIPK3.

Journal of ginseng research·2026

Related Experiment Video

Updated: Aug 21, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

1.7K

Motion estimation for large displacements and deformations.

Qiao Chen1, Charalambos Poullis2

  • 1Immersive and Creative Technologies Lab, Concordia University, Montreal, QC, Canada.

Scientific Reports
|November 17, 2022
PubMed
Summary

HybridFlow is a novel variational motion estimation framework designed for large displacements and deformations. It achieves robust and accurate optical flow estimation without requiring training, outperforming existing methods on benchmark datasets.

More Related Videos

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.3K
Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
14:14

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Published on: April 16, 2017

11.7K

Related Experiment Videos

Last Updated: Aug 21, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

1.7K
Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.3K
Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
14:14

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Published on: April 16, 2017

11.7K

Area of Science:

  • Computer Vision
  • Image Analysis
  • Motion Estimation

Background:

  • Variational optical flow methods struggle with large displacements, deformations, and noise.
  • Existing techniques are sensitive to sparse match quality and local optimization limitations.

Purpose of the Study:

  • To introduce HybridFlow, a variational motion estimation framework for handling large displacements and deformations.
  • To improve the robustness and accuracy of optical flow estimation in challenging scenarios.

Main Methods:

  • A multi-scale hybrid matching approach using coarse-scale clusters and fine-scale superpixels.
  • Multi-scale graph matching and localized feature matching for initial flow estimation.
  • Edge-preserving interpolation and variational refinement for flow propagation.

Main Results:

  • HybridFlow demonstrates superior performance compared to state-of-the-art variational techniques.
  • Achieves comparable results to deep-learning-based methods on benchmark datasets.
  • Exhibits robustness to substantial displacements and various transformations.

Conclusions:

  • HybridFlow offers a robust and effective solution for large displacement optical flow.
  • The framework's ability to handle arbitrary graph topologies enhances motion estimation with significant deformations.
  • Ideal for large-scale imagery like aerial images due to its training-free and robust nature.