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

Airborne LiDAR Point Cloud Classification Using Ensemble Learning for DEM Generation.

Sensors (Basel, Switzerland)·2024
Same author

Relaxation-Based Radiometric Normalization for Multitemporal Cross-Sensor Satellite Images.

Sensors (Basel, Switzerland)·2023
Same author

Spectral Feature Selection Optimization for Water Quality Estimation.

International journal of environmental research and public health·2020
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: Aug 30, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.1K

Dual Guided Aggregation Network for Stereo Image Matching.

Ruei-Ping Wang1, Chao-Hung Lin1

  • 1Department of Geomatics, National Cheng-Kung University, Tainan City 701, Taiwan.

Sensors (Basel, Switzerland)
|August 26, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces the Dual Guided Aggregation Network (Dual-GANet) for improved stereo image matching in 3D reconstruction. The novel network enhances accuracy by using bidirectional matching and a unique regression technique, outperforming existing models.

Keywords:
deep learningdense image matchingleft–right consistency

More Related Videos

Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves
06:26

Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves

Published on: January 12, 2024

479
Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion
10:30

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

Published on: September 4, 2013

9.7K

Related Experiment Videos

Last Updated: Aug 30, 2025

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.1K
Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves
06:26

Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves

Published on: January 12, 2024

479
Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion
10:30

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

Published on: September 4, 2013

9.7K

Area of Science:

  • Computer Vision
  • Photogrammetry
  • Artificial Intelligence

Background:

  • Stereo image dense matching is crucial for 3D reconstruction but remains challenging.
  • Deep convolutional neural networks have advanced stereo matching.
  • Existing methods often struggle with pixel mismatch and occlusions.

Purpose of the Study:

  • To propose a novel network, the Dual Guided Aggregation Network (Dual-GANet), for enhanced stereo image dense matching.
  • To reduce pixel mismatch and improve accuracy in 3D reconstruction.
  • To introduce innovative techniques for learning invisible-to-visible and left-right consistent matching.

Main Methods:

  • Developed the Dual-GANet utilizing both left-to-right and right-to-left image matchings.
  • Implemented flipped training with cost volume consistentization for improved matching.
  • Introduced suppressed multi-regression to refine disparity probability distribution.
  • Adapted the GANet backbone with modifications for guided aggregation, disparity regression, and loss functions.

Main Results:

  • The Dual-GANet demonstrated superior performance on SceneFlow and KITTI2015 datasets compared to the backbone model.
  • Achieved lower average End-Point-Error (EPE) and pixel Error Rate (ER) for both datasets.
  • Specifically, Dual-GANet achieved EPE of 0.418 and ER (>1 pixel) of 5.81% on SceneFlow.

Conclusions:

  • The proposed Dual-GANet significantly improves stereo image dense matching accuracy.
  • The bidirectional matching and suppressed multi-regression techniques are effective.
  • Dual-GANet offers a robust and applicable solution for 3D reconstruction tasks.