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

Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

661
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
661
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

627
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
627
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

191
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
191
Three-Dimensional Analysis of Strain01:29

Three-Dimensional Analysis of Strain

212
Three-dimensional strain analysis is crucial for understanding how materials deform under stress, particularly in elastic, homogeneous materials. This method employs principal stress axes to simplify complex stress states into more understandable forms. Subjected to stress, a small cubic element within a material either expands or contracts along these axes, transforming into a rectangular parallelepiped. This transformation effectively illustrates the material's deformation. The principal...
212
Deconvolution01:20

Deconvolution

154
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
154
Three-Dimensional Force System01:30

Three-Dimensional Force System

2.0K
In mechanical engineering, a three-dimensional force system is a system of forces acting in three dimensions, with forces applied along the x, y, and z coordinate axes. The three-dimensional force system is an important concept in mechanical engineering, as it allows engineers to understand and analyze the behavior of objects and structures in three dimensions. By understanding the forces acting on a system, engineers can design more efficient and effective mechanical systems that can withstand...
2.0K

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

Genomic characteristics of a <i>Streptococcus suis</i> of ST353 resulting in severe endophthalmitis with bilateral deafness.

Infectious diseases & immunity·2026
Same author

Efficient and accurate neural-field reconstruction using resistive memory.

Nature·2026
Same author

Precise zonal diagnosis: multi-b-value DWI model reveals differential predictors of clinically significant prostate cancer in peripheral and transition zones.

Insights into imaging·2026
Same author

Resistive memory-based neural differential equation solver for score-based diffusion model.

Nature communications·2026
Same author

Cell membrane-targeting AIE probe for Cancer and inflammatory imaging.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2026
Same author

Toward on-site analysis: a paper-based luminescent metal organic framework sensing strategy for sulfide via chemical vapor generation-colorimetric system.

Analytical and bioanalytical chemistry·2026
Same journal

Application of ephrin-B2 loaded glycol chitosan-silk fibroin hydrogel in the treatment of diabetic refractory wounds.

Scientific reports·2026
Same journal

International expert Delphi consensus on thromboprophylaxis in metabolic and bariatric surgery.

Scientific reports·2026
Same journal

Assessing the cross-region knowledge transfer capability of selected deep learning building vectorization methods in the context of available training datasets.

Scientific reports·2026
Same journal

Feasibility and preliminary effects of outdoor versus indoor cognitive-motor therapy in women with Alzheimer's disease: A randomized single-blind pilot study.

Scientific reports·2026
Same journal

Hallmarks of social action in the vocal turn-taking of wild common marmosets (Callithrix jacchus).

Scientific reports·2026
Same journal

Role and mechanism of AOPPs-induced NOX4-mediated ferroptosis in intervertebral disc degeneration.

Scientific reports·2026
查看所有相关文章

相关实验视频

Updated: Jun 23, 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

2.0K

联合立体声3D物体检测和隐性表面重建.

Shichao Li1, Xijie Huang2, Zechun Liu3

  • 1Department of Computer Science and Engineering, HKUST, Hong Kong, SAR, 999077, China. nicholas.li@connect.ust.hk.

Scientific reports
|June 17, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了S-3D-RCNN,这是一种用于精确的3D对象定向和从立体图像中隐式形状恢复的新框架. 它使用中间几何表示 (IGRs) 来增强3D场景的理解.

更多相关视频

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

12.8K
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

383

相关实验视频

Last Updated: Jun 23, 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

2.0K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

12.8K
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

383

科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 三维重建的3D重建

背景情况:

  • 精确的3D对象定向和图像的形状估计对于自主系统至关重要.
  • 现有的方法经常在精确的方向恢复和详细的形状预测方面扎,特别是在看不见的表面.

研究的目的:

  • 开发一种基于学习的框架 (S-3D-RCNN),用于在SO3中准确的对象定向和从立体RGB图像中隐含的刚性形状预测.
  • 引入中间几何表示 (IGRs) 以改进方向估计,并解决形状预测中看不见表面的幻觉.

主要方法:

  • 提出了一种使用中间几何表示 (IGRs) 进行自我中心对象方向估计的渐进式方法.
  • 开发了一个深度模型,将图像强度转换为对象部分坐标.
  • 通过基于点的表示来研究隐性形状估计,增强IGR来处理看不见的表面.

主要成果:

  • 在3D场景理解方面,S-3D-RCNN表现出卓越的性能.
  • 拟议的IGR被验证为其在方向和形状恢复方面的有效性.
  • 设计并应用了新的指标来评估KITTI基准上的隐性形状估计.

结论:

  • 该S-3D-RCNN框架有效地从立体图像中恢复准确的对象定向和隐含的刚性形状.
  • 中间几何表示 (IGRs) 显著提高了3D场景理解能力.
  • 该研究为从视觉数据中重建3D对象提供了新的方法和评估指标.