Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Study on dual-layer MPC-SMC control strategy for piezoelectric platforms based on extended kalman filter.

ISA transactions·2026
Same author

MMSDF: multimodal sparse dense fusion for 3D object detection.

Applied optics·2026
Same author

Wholly-WOOD: Wholly Leveraging Diversified-Quality Labels for Weakly-Supervised Oriented Object Detection.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Accurate 3D Measurement of Complex Texture Objects by Height Compensation Using a Dual-Projector Structure.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2024
Same author

On Boundary Discontinuity in Angle Regression Based Arbitrary Oriented Object Detection.

IEEE transactions on pattern analysis and machine intelligence·2024
Same author

Defocused projection model for phase-shifting profilometry with a large depth range.

Optics express·2021

相关实验视频

Updated: Jun 11, 2025

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip
14:09

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

Published on: November 16, 2019

6.9K

在3D重建中的间接照明的错误模型和简洁的时间网络.

Yuchong Chen, Pengcheng Yao, Rui Gao

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |October 8, 2024
    PubMed
    概括
    此摘要是机器生成的。

    本研究引入了一种新的方法来纠正3D重建中的间接照明错误. 该方法使用在模拟数据上训练的多层感知器来提高半透明物体的3D点云精度.

    更多相关视频

    Anatomically Inspired Three-dimensional Micro-tissue Engineered Neural Networks for Nervous System Reconstruction, Modulation, and Modeling
    10:45

    Anatomically Inspired Three-dimensional Micro-tissue Engineered Neural Networks for Nervous System Reconstruction, Modulation, and Modeling

    Published on: May 31, 2017

    13.0K
    Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain
    06:52

    Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain

    Published on: January 26, 2024

    1.9K

    相关实验视频

    Last Updated: Jun 11, 2025

    High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip
    14:09

    High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

    Published on: November 16, 2019

    6.9K
    Anatomically Inspired Three-dimensional Micro-tissue Engineered Neural Networks for Nervous System Reconstruction, Modulation, and Modeling
    10:45

    Anatomically Inspired Three-dimensional Micro-tissue Engineered Neural Networks for Nervous System Reconstruction, Modulation, and Modeling

    Published on: May 31, 2017

    13.0K
    Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain
    06:52

    Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain

    Published on: January 26, 2024

    1.9K

    科学领域:

    • 机器人和人工智能 机器人和人工智能
    • 计算机视觉 计算机视觉
    • 光学计量学 在光学计量学

    背景情况:

    • 3D重建对于机器人和人工智能应用至关重要.
    • 边缘投影造型测量是一种常见的3D成像技术.
    • 半透明物体由于间接照明而带来挑战,降低了重建的准确性.

    研究的目的:

    • 开发一种快速准确的方法来纠正3D重建中的间接照明错误.
    • 为了提高从半透明物体生成的3D点云的精度.

    主要方法:

    • 基于精确的错误模型设计了一个新的网络架构.
    • 间接照明错误被转化为正弦数列.
    • 采用多层感知子来纠错错误,其性能优于传统方法和CNN.

    主要成果:

    • 拟议的网络有效地纠正了间接照明引起的错误.
    • 实验证明了网络在模拟和现实数据上的效率.
    • 多层感知器在错误纠正方面表现出卓越的性能.

    结论:

    • 开发的方法显著提高了半透明物体的3D重建精度.
    • 正弦序列误差模型和多层感知子为间接照明提供了强大的解决方案.
    • 这种方法为需要从具有挑战性的材料中获得精确3D数据的应用提供了有价值的工具.