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

You might also read

Related Articles

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

Sort by
Same author

DGCFNet: Dual Global Context Fusion Network for remote sensing image semantic segmentation.

PeerJ. Computer science·2025
Same author

Scene Text Detection Based on Two-Branch Feature Extraction.

Sensors (Basel, Switzerland)·2022
Same author

AAF-Net: Scene text detection based on attention aggregation features.

PloS one·2022
Same author

ARDformer: Agroforestry Road Detection for Autonomous Driving Using Hierarchical Transformer.

Sensors (Basel, Switzerland)·2022
Same author

Detection of Pine Wilt Nematode from Drone Images Using UAV.

Sensors (Basel, Switzerland)·2022
Same author

Infrared Small Target Detection Using Regional Feature Difference of Patch Image.

Sensors (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 30, 2025

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

15.0K

Multi-Feature Single Target Robust Tracking Fused with Particle Filter.

Caihong Liu1, Mayire Ibrayim1, Askar Hamdulla1

  • 1College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.

Sensors (Basel, Switzerland)
|March 10, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a robust particle filter-based algorithm for long-term single-target tracking in complex scenes. It enhances tracking accuracy and stability by fusing multiple features and incorporating a re-detection module.

Keywords:
adaptive filter updateadaptive learning rate updatecorrelation filteringmulti-feature fusionparticle filter re-detection

More Related Videos

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics
13:30

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics

Published on: February 18, 2022

4.6K
High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy
15:13

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Published on: July 25, 2014

11.5K

Related Experiment Videos

Last Updated: Sep 30, 2025

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

15.0K
Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics
13:30

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics

Published on: February 18, 2022

4.6K
High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy
15:13

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Published on: July 25, 2014

11.5K

Area of Science:

  • Computer Vision
  • Machine Learning

Background:

  • Long-term single-target tracking in complex scenes faces challenges like target deformation, occlusion, and fast motion, leading to model drift.
  • Existing methods struggle with maintaining robust tracking performance under these challenging conditions.

Purpose of the Study:

  • To develop a robust multi-feature single-target tracking algorithm using a particle filter to address the limitations of current tracking methods.
  • To improve tracking accuracy and robustness in complex scenarios through feature fusion and adaptive model updates.

Main Methods:

  • The algorithm utilizes a correlation filtering framework, fusing manual features (Histogram of Oriented Gradients, color histograms) with deep features from VGGNet-19.
  • A re-detection module based on a fused particle filter is designed to recover accurate tracking after failures.
  • Adaptive learning rate and filter updates are implemented for enhanced target model accuracy.

Main Results:

  • The proposed algorithm demonstrates effective long-term tracking in complex scenes across OTB-2015, OTB-2013, and UAV123 datasets.
  • Experimental results indicate significantly improved tracking stability and accuracy compared to existing methods.

Conclusions:

  • The multi-feature fusion and particle filter-based approach provides a robust solution for challenging single-target tracking scenarios.
  • The algorithm effectively overcomes issues of target model drift and loss, ensuring reliable long-term tracking performance.