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

Transformation of Plane Strain01:12

Transformation of Plane Strain

162
When analyzing elongated structures like bars subjected to uniformly distributed loads, it is essential to understand the transformation of plane strain when coordinate axes are rotated. This transformation helps to assess how material deformation characteristics vary with orientation, which is crucial in materials science and structural engineering.
Under plane strain conditions, typical for members where one dimension significantly exceeds the others, deformations and resultant strains are...
162
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

646
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.
646
Vector Transformation in Rotating Coordinate Systems01:16

Vector Transformation in Rotating Coordinate Systems

1.6K
Consider a vector rotating about an axis with an angular velocity, such that its tip sweeps a circular path.
1.6K
Transformation of Plane Stress01:18

Transformation of Plane Stress

228
Studying stress transformation is essential in understanding how stress components within a material, like a cube under plane stress, change with rotation. This change is analyzed by considering a prismatic element within the cube. As the element rotates, the stress components acting on it—both normal and shearing stresses—change in magnitude and orientation. This change is quantified using trigonometric functions of the rotation angle, relating the forces acting on the rotated element's...
228
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

300
Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
300

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

Prediction model for periodontitis stage based on the salivary microbiome.

mSystems·2026
Same author

Genome of <i>Raphanus sativus</i> L<i>.</i> Bakdal, an elite line of large cultivated Korean radish.

Frontiers in genetics·2024
Same author

Learning to Discriminate Information for Online Action Detection: Analysis and Application.

IEEE transactions on pattern analysis and machine intelligence·2022
Same author

Motion Blur Kernel Rendering Using an Inertial Sensor: Interpreting the Mechanism of a Thermal Detector.

Sensors (Basel, Switzerland)·2022
Same author

Blind Deblurring of Text Images Using a Text-Specific Hybrid Dictionary.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2019
Same author

Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.

Computer methods and programs in biomedicine·2018

相关实验视频

Updated: Jun 30, 2025

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
08:04

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

4.5K

桥梁隐式和显式几何转换为单图像视图合成.

Byeongjun Park, Hyojun Go, Changick Kim

    IEEE transactions on pattern analysis and machine intelligence
    |March 19, 2024
    PubMed
    概括

    这项研究引入了一种高效的非自行回归模型,用于单图像视图合成,解决了"摇摆"问题. 它通过补充显式和隐式3D几何表示,比以前的方法更快地生成高质量的新视图.

    科学领域:

    • 计算机视觉 计算机视觉
    • 计算机图形 计算机图形
    • 人工智能的人工智能

    背景情况:

    • 单图像视图合成旨在从单个输入图像中生成新的视角.
    • 自动回归模型实现高质量的新视图,但在内容保存和现实完成之间面临一个权衡 ("摇摆"问题),并且在计算上昂贵.

    研究的目的:

    • 为单图像视图合成提出一个高效的非自行回归框架.
    • 通过有效地结合显式和隐式3D几何表示来减轻"摇摆"问题.
    • 显著降低与新型视图生成相关的计算成本.

    主要方法:

    • 开发了一个新的损失函数来补充显式和隐式染器.
    • 损失函数鼓励明确的特征来增强重新设计的区域和隐性特征来改善视野之外的区域.
    • 使用了一种高效的非自行回归模型架构.

    主要成果:

    • 成功地缓解了单图像视图合成中的"摇摆"问题.
    • 与自动回归最先进的方法相比,实现了更高的性能.
    • 创建新视图的速度大约是现有方法的100倍.
    • 在RealEstate10K和ACID数据集上验证了有效性和效率.

    更多相关视频

    Quantifying Intermembrane Distances with Serial Image Dilations
    07:45

    Quantifying Intermembrane Distances with Serial Image Dilations

    Published on: September 28, 2018

    6.4K
    Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
    14:14

    Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

    Published on: April 16, 2017

    11.6K

    相关实验视频

    Last Updated: Jun 30, 2025

    Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
    08:04

    Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

    Published on: December 4, 2013

    4.5K
    Quantifying Intermembrane Distances with Serial Image Dilations
    07:45

    Quantifying Intermembrane Distances with Serial Image Dilations

    Published on: September 28, 2018

    6.4K
    Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
    14:14

    Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

    Published on: April 16, 2017

    11.6K

    结论:

    • 拟议的框架为单图像视图合成提供了有效和高效的解决方案.
    • 新的损失函数成功地平衡了内容保存和现实的完成.
    • 非自行回归模型可以在显著降低计算开销的情况下实现竞争性或优异的结果.