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

Mesh-guided optimized retexturing for image and video.

Yanwen Guo1, Hanqiu Sun, Qunsheng Peng

  • 1National Laboratory for Novel Software Technology, Nanjing University, Nanjing, People's Republic of China. ywguo@nju.edu.cn

IEEE Transactions on Visualization and Computer Graphics
|January 15, 2008
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

Identifying Multicomponent Microplastics in Complex Matrices Using a Fast Fourier Convolutional Neural Network with Hierarchical Feature Mapping.

Environmental science & technology·2026
Same author

Development and application of a VNAR-based detection nanobody for avian influenza virus H9N2.

Frontiers in immunology·2026
Same author

Surface Reconstruction From Point Clouds via Image-Free Point-to-Gaussian Inference.

IEEE transactions on visualization and computer graphics·2026
Same author

GSReuse: Temporally Adaptive Screen-Space Reuse for Accelerating 3D Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same author

TFAM-Associated Mitochondrial Dynamics and Metabolic Reprogramming Regulate Microglial Polarization: Temporal and Causal Perspectives.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2026
Same author

Epigenetic H3K4me3 activation of miR-155-5p promotes intervertebral disc degeneration via autophagy and ageing in nucleus pulposus cells.

Non-coding RNA research·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
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

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

This study introduces a novel method for image and video retexturing using stretch-based mesh optimization. The approach effectively preserves geometric distortions and lighting, enabling seamless texture replacement for visually pleasing results.

Area of Science:

  • Computer Vision
  • Computer Graphics
  • Image Processing

Background:

  • Texture replacement in images and videos is challenging due to geometric distortions and lighting variations.
  • Existing methods often struggle with maintaining visual fidelity and handling temporal consistency in videos.

Purpose of the Study:

  • To develop an efficient and robust approach for texture replacement in both static images and dynamic videos.
  • To ensure retextured outputs accurately reflect the original geometry, lighting, and motion characteristics.

Main Methods:

  • Image retexturing utilizes stretch-based mesh parametrization with normal information for perspective distortion and Poisson-based refinement for fine-scale details.
  • Color transfer in YCbCr color space preserves luminance, and the method is independent of the replacement texture.

Related Experiment Videos

  • Video retexturing employs a key-frame-based approach with local motion optimization and graph-cut segmentation to address optical flow inaccuracies and temporal smoothing.

    • Main Results:

    • The proposed method generates retextured images and videos with accurate distortion and shading effects consistent with the underlying scene.
    • It effectively handles texture distortion at fine scales and preserves luminance.
    • Video retexturing alleviates visibility shifting and texture drifting, producing visually pleasing results with temporal coherence.

    Conclusions:

    • The developed stretch-based mesh optimization approach offers a versatile solution for image and video retexturing.
    • The key-frame-based video extension successfully addresses challenges in motion tracking and temporal consistency.
    • The method demonstrates its capability to produce high-quality, visually convincing retexturing results across different media.