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 - 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...
Vector Functions and Motion: Problem Solving01:30

Vector Functions and Motion: Problem Solving

Accurate position tracking is fundamental to the safe and effective operation of unmanned aerial vehicles (UAVs), particularly during precision maneuvers near complex structures. In this scenario, a drone is programmed to perform a high-precision inspection of a vertical structure, starting at position ((x, y, z) = (3, 0, 0)), with an initial velocity oriented in the positive z-direction. The trajectory of the drone is governed by a time-dependent acceleration function a(t), which is predefined...

You might also read

Related Articles

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

Sort by
Same author

Minimally invasive prediction of blood lactate during incremental exercise via heart rate, core body temperature, and sweat-derived indices.

Scientific reports·2026
Same author

Elucidation of Enhanced Lysine Sensing via Pt-Functionalized 2D WS<sub>2</sub> for Biosensing Applications.

ACS applied materials & interfaces·2026
Same author

PD-L1 mRNA expression correlates with tumor growth rate in giant cell tumor of bone: a volumetric MRI analysis.

BMC musculoskeletal disorders·2026
Same author

Diffusion-based skin disease data augmentation with fine-grained detail preservation and interpolation for data diversity.

PloS one·2025
Same author

Correction: Discovery of genes positively modulating treatment effect using potential outcome framework and Bayesian update.

BMC medical informatics and decision making·2025
Same author

Selective denoising autoencoder for classification of noisy gas mixtures using 2D transition metal dichalcogenides.

Talanta·2024

Related Experiment Video

Updated: Jun 14, 2026

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

12.5K

Efficient Single-Shot Multi-Object Tracking for Vehicles in Traffic Scenarios.

Youngkeun Lee1, Sang-Ha Lee1, Jisang Yoo1

  • 1Department of Electronic Engineering, Kwangwoon University, Seoul 01897, Korea.

Sensors (Basel, Switzerland)
|October 13, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces an enhanced single-shot system for multi-object tracking, improving accuracy and maintaining high inference speed. The advanced model achieves state-of-the-art performance on the UA-DETRAC dataset for both object detection and tracking tasks.

Keywords:
multi-object trackingobject detectionsingle-shottraffic scenariovehicle tracking

More Related Videos

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.1K
SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
08:13

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware

Published on: December 25, 2017

8.3K

Related Experiment Videos

Last Updated: Jun 14, 2026

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

12.5K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.1K
SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
08:13

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware

Published on: December 25, 2017

8.3K

Area of Science:

  • Computer Vision
  • Deep Learning
  • Artificial Intelligence

Background:

  • Multi-object tracking is crucial for video surveillance and analysis.
  • Current deep learning methods face a trade-off between accuracy and inference speed.
  • Two-stage methods suffer from slow inference due to sequential detection and embedding extraction.

Purpose of the Study:

  • To propose an enhanced single-shot multi-object tracking system.
  • To improve tracking accuracy while maintaining high inference speed.
  • To overcome the limitations of existing single-shot and two-stage tracking methods.

Main Methods:

  • Developed a single-shot system integrating object detection and appearance embedding extraction.
  • Employed strong feature extraction and fusion techniques.
  • Evaluated the system on the UA-DETRAC dataset.

Main Results:

  • Achieved an Average Precision (AP) score of 69.93% for object detection, outperforming FairMOT and JDE.
  • Obtained a Multi-Object Tracking Accuracy (MOTA) score of 68.5%.
  • Reached a Precision and Recall-based MOTA (PR-MOTA) score of 24.5%, surpassing prior state-of-the-art trackers.

Conclusions:

  • The proposed enhanced single-shot system significantly improves multi-object tracking performance.
  • The method effectively balances high accuracy with efficient inference speed.
  • This work sets a new benchmark for single-shot multi-object tracking systems.