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 Experiment Videos

MC-NeRF: Multi-Camera Neural Radiance Fields for Multi-Camera Image Acquisition Systems.

Yu Gao, Lutong Su, Hao Liang

    IEEE Transactions on Visualization and Computer Graphics
    |March 3, 2025
    PubMed
    Summary
    This summary is machine-generated.

    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

    Single-cell RNA-seq reveals mRNAs and lncRNAs important for oocytes in vitro matured in pigs.

    Reproduction in domestic animals = Zuchthygiene·2021
    Same author

    Effects of the histone acetylase inhibitor C646 on growth and differentiation of adipose-derived stem cells.

    Cell cycle (Georgetown, Tex.)·2021
    Same author

    A Method for Estimating 24-Hour Urinary Sodium Excretion by Casual Urine Specimen in Chinese Hypertensive Patients.

    American journal of hypertension·2021
    Same author

    <i>Scutellaria baicalensis</i> extract and baicalein inhibit replication of SARS-CoV-2 and its 3C-like protease <i>in vitro</i>.

    Journal of enzyme inhibition and medicinal chemistry·2021
    Same author

    Frequent reassortment and potential recombination shape the genetic diversity of influenza D viruses.

    The Journal of infection·2021
    Same author

    Evaluation of origanum oil, hydrolysable tannins and tea saponin in mitigating ruminant methane: In vitro and in vivo methods.

    Journal of animal physiology and animal nutrition·2021
    Same journal

    Two-phase Impulse Fluid on Particle Flow Map.

    IEEE transactions on visualization and computer graphics·2026
    Same journal

    FGO-SLAM++: Real-time Geometry-Aware Gaussian SLAM with Continuous Opacity Field.

    IEEE transactions on visualization and computer graphics·2026
    Same journal

    Blue Noise Dithering for Reservoir-based Spatio-temporal Importance Resampling.

    IEEE transactions on visualization and computer graphics·2026
    Same journal

    ROS-GS: Relightable Outdoor Scenes With Gaussian Splatting.

    IEEE transactions on visualization and computer graphics·2026
    Same journal

    MesoSplats: Texture Synthesis with Gaussian Splatting.

    IEEE transactions on visualization and computer graphics·2026
    Same journal

    GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

    IEEE transactions on visualization and computer graphics·2026
    See all related articles

    MC-NeRF optimizes intrinsic and extrinsic camera parameters for Neural Radiance Fields (NeRF) in multi-camera systems. This method improves 3D scene reconstruction accuracy with varying camera setups.

    Area of Science:

    • Computer Vision
    • 3D Reconstruction
    • Machine Learning

    Background:

    • Neural Radiance Fields (NeRF) excel at 3D scene representation using multi-view images.
    • Multi-camera systems present challenges for NeRF due to varying intrinsic/extrinsic parameters and pose changes.
    • Existing NeRF methods often assume a single camera or struggle with parameter optimization in multi-camera scenarios.

    Purpose of the Study:

    • To develop a novel method, MC-NeRF, for joint optimization of intrinsic and extrinsic parameters within NeRF for multi-camera systems.
    • To address the challenges of varying camera parameters and poor initialization in NeRF-based 3D scene reconstruction.
    • To enable accurate 3D representation from multi-view images captured by individual cameras with distinct parameters.

    Main Methods:

    Related Experiment Videos

    • Introduced MC-NeRF for joint optimization of NeRF, intrinsic, and extrinsic parameters, allowing per-image camera configurations.
    • Proposed a decoupling constraint using auxiliary images to resolve the coupling issue between intrinsic and extrinsic parameter optimization.
    • Developed an efficient auxiliary image acquisition scheme to mitigate degenerate cases during parameter decoupling and introduced a new dataset.

    Main Results:

    • MC-NeRF demonstrates superior performance in scenarios with diverse camera parameters compared to baseline methods.
    • Achieved significant improvements in intrinsic parameter estimation, extrinsic parameter estimation, and scale estimation.
    • Showcased enhanced rendering quality for 3D scenes reconstructed from multi-camera data.

    Conclusions:

    • MC-NeRF effectively handles joint optimization of camera parameters for NeRF in complex multi-camera setups.
    • The proposed decoupling strategy and auxiliary image scheme are crucial for robust parameter estimation.
    • The method provides a robust solution for accurate 3D scene reconstruction using multi-view images from systems with varying camera characteristics.