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

Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

375
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
375
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

285
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
285
Velocity and Acceleration in Steady and Unsteady Flow01:11

Velocity and Acceleration in Steady and Unsteady Flow

264
In fluid mechanics, velocity and acceleration are key concepts for analyzing particle motion in both steady and unsteady flow. Consider a fluid particle moving along a pathline, where its velocity depends on its position and time. The particle's acceleration is obtained by differentiating the velocity with respect to time.
The acceleration can be generalized to any point in the flow, and expressed as components along three perpendicular directions, representing changes in velocity over...
264
Gradually Varying Flow01:29

Gradually Varying Flow

256
Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...
256
Streamlines, Streaklines, and Pathlines01:18

Streamlines, Streaklines, and Pathlines

1.7K
A streamline represents the trajectory that is always tangent to the fluid's velocity vector at any given point. The velocity of a fluid particle is always directed along the streamline, ensuring the particle continuously follows the streamline's path. Streamlines are particularly useful for visualizing the overall direction of flow in a fluid system, and they provide an instantaneous representation of the flow's velocity field. In steady flow, where conditions do not change over...
1.7K
Eulerian and Lagrangian Flow Descriptions01:22

Eulerian and Lagrangian Flow Descriptions

1.7K
Fluid flow analysis is critical in many scientific and engineering disciplines, and two principal approaches are used to describe this flow: the Eulerian and Lagrangian methods. These methods offer different perspectives on monitoring and analyzing the motion of fluids, each with distinct advantages depending on the scenario.
The Eulerian method focuses on fixed points in space where fluid properties, such as velocity, pressure, and temperature, are observed as the fluid moves between these...
1.7K

You might also read

Related Articles

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

Sort by
Same author

Pharmacogenomic profiling of the efficacy of gemcitabine monotherapy in metastatic pancreatic cancer: Subgroup analysis of the GENESECT study.

British journal of clinical pharmacology·2026
Same author

Biomimetic Microfibers for Myelin-Enhancer Screening and Neural Regeneration.

Cyborg and bionic systems (Washington, D.C.)·2026
Same author

Antiemetic Efficacy of Dexamethasone Omission in Antiemetic Therapy During Highly Emetogenic Chemotherapy for Breast Cancer.

Die Pharmazie·2026
Same author

Stable Au(III) Benzohomoporphyrin: Synthesis, Structure, Near-Infrared Absorption, and Superoxide Radical Generation.

Inorganic chemistry·2026
Same author

Altered kinship vocal dynamics in marmosets with valproic acid-induced model of autism.

iScience·2026
Same author

Usefulness of pharmacy outpatient clinic follow-up for maintaining relative dose intensity in patients on adjuvant CAPOX chemotherapy for gastric cancer.

Molecular and clinical oncology·2026

Related Experiment Video

Updated: Nov 24, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

16.9K

Visualization by P-flow: gradient- and feature-based optical flow and vector fields extracted from image analysis.

Wataru Suzuki, Atsushi Hiyama, Noritaka Ichinohe

    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
    |December 28, 2020
    PubMed
    Summary
    This summary is machine-generated.

    We developed pseudo-flow (P-flow) to extract optical flow for visualization from movies. This method combines feature tracking and gradient-based approaches, improving motion vector extraction.

    More Related Videos

    Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
    11:00

    Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

    Published on: July 19, 2016

    11.8K
    Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods
    09:17

    Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods

    Published on: April 23, 2018

    11.0K

    Related Experiment Videos

    Last Updated: Nov 24, 2025

    Determining 3D Flow Fields via Multi-camera Light Field Imaging
    14:25

    Determining 3D Flow Fields via Multi-camera Light Field Imaging

    Published on: March 6, 2013

    16.9K
    Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
    11:00

    Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

    Published on: July 19, 2016

    11.8K
    Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods
    09:17

    Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods

    Published on: April 23, 2018

    11.0K

    Area of Science:

    • Computer Vision
    • Neuroscience
    • Image Processing

    Background:

    • Optical flow extraction is crucial for motion analysis in videos.
    • Existing methods like feature tracking and gradient-based approaches have limitations.

    Purpose of the Study:

    • To introduce pseudo-flow (P-flow), a novel method for extracting optical flow suitable for visualization from natural movies.
    • To analyze the classification and underlying principles of the P-flow algorithm.

    Main Methods:

    • The P-flow algorithm involves two stages: local motion vector field extraction and vector tracking between frames.
    • The study demonstrates P-flow integrates feature (vector) tracking with gradient-based principles.
    • Incorporation of interpolation and a corner detector to enhance robustness.

    Main Results:

    • P-flow is shown to satisfy the brightness constancy constraint, characteristic of gradient-based methods.
    • The combined approach addresses limitations inherent in traditional optical flow techniques.
    • The method provides effective optical flow extraction for visualization purposes.

    Conclusions:

    • Pseudo-flow offers a robust and versatile approach to optical flow extraction.
    • The integration of diverse techniques enhances the accuracy and applicability of motion vector analysis.
    • P-flow is a valuable tool for visualizing motion in natural movies, with implications for neuroscience research.