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

Reducing Line Loss01:18

Reducing Line Loss

184
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
184
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

497
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...
497
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

428
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...
428
Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

14.2K
Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
14.2K
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

365
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...
365
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

387
A slider-crank mechanism 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. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
387

You might also read

Related Articles

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

Sort by
Same author

Hierarchical alterations of brain network coupling and its clinical and cognitive relevance in systemic lupus erythematosus.

Progress in neuro-psychopharmacology & biological psychiatry·2026
Same author

Improving the quality attributes of potato starch gel through combined pre-drying and short-term retrogradation.

International journal of biological macromolecules·2026
Same author

Activity of octyl gallate against drug-sensitive and buparvaquone-resistant Theileria annulata.

International journal for parasitology. Drugs and drug resistance·2026
Same author

Ultrasound-assisted enzymatic extraction and properties of polysaccharide from <i>Nostoc commune</i>.

Food chemistry: X·2026
Same author

A spatially confined "double-key lock" smart DNA hydrogel for dynamic detection of MicroRNA in cells.

Chemical science·2026
Same author

Bioartificial Livers Developed From Gene-Edited Pig Hepatocyte Organoids Improve Amino Acid and Lipid Profiles in the Plasma of Patients With Liver Failure.

MedComm·2026

Related Experiment Video

Updated: Aug 6, 2025

FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis
10:02

FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis

Published on: December 24, 2014

11.8K

Pedestrian multiple-object tracking based on FairMOT and circle loss.

Jin Che1,2, Yuting He3,4, Jinman Wu1,2

  • 1School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan, 750021, China.

Scientific Reports
|March 21, 2023
PubMed
Summary

This study introduces an improved multi-object tracking algorithm using FairMOT and Circle Loss, significantly reducing pedestrian ID switches. The enhanced method achieves better accuracy in complex scenarios for computer vision applications.

More Related Videos

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
08:32

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Published on: June 15, 2020

12.6K
Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.6K

Related Experiment Videos

Last Updated: Aug 6, 2025

FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis
10:02

FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis

Published on: December 24, 2014

11.8K
Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
08:32

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Published on: June 15, 2020

12.6K
Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.6K

Area of Science:

  • Computer Vision
  • Artificial Intelligence

Background:

  • Multi-object tracking (MOT) is crucial in computer vision.
  • Occlusions in practical applications cause frequent pedestrian ID switches, degrading tracking performance.

Purpose of the Study:

  • To develop a robust multi-object tracking algorithm that minimizes ID switches.
  • To enhance pedestrian feature distinctiveness for improved re-identification.

Main Methods:

  • Utilized HRNet as the baseline architecture.
  • Integrated Polarized Self-Attention into HRNet-w32 for better information weighting.
  • Optimized the re-identification branch using Circle Loss for discriminative feature learning.

Main Results:

  • Achieved a MOTA score of 69.5% and an IDF1 score of 70.0% on the MOT17 dataset.
  • Reduced the number of ID switches by 636 compared to the TraDes algorithm.

Conclusions:

  • The proposed FairMOT and Circle Loss-based algorithm effectively addresses ID switches in multi-object tracking.
  • The integration of Polarized Self-Attention and Circle Loss leads to more accurate and robust pedestrian tracking.