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相关概念视频

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

1.8K
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.
1.8K
Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

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Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
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Gestalt Principles of Perception01:21

Gestalt Principles of Perception

1.0K
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...
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相关实验视频

Updated: Jan 10, 2026

Controlled Rotation of Human Observers in a Virtual Reality Environment
09:11

Controlled Rotation of Human Observers in a Virtual Reality Environment

Published on: April 21, 2022

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MOA:在VR中高效的场景感知多对象排列.

Xuehuai Shi, Yuhan Duan, Ziteng Wang

    IEEE transactions on visualization and computer graphics
    |November 24, 2025
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了虚拟现实中3D多对象排列的高效方法,改善了复杂,封闭的场景中的选择和操纵. 新方法提高了虚拟环境中的任务效率和用户体验.

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    A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
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    A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

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    Photorealistic Learned Landscapes for Augmented Reality
    06:54

    Photorealistic Learned Landscapes for Augmented Reality

    Published on: June 27, 2025

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    相关实验视频

    Last Updated: Jan 10, 2026

    Controlled Rotation of Human Observers in a Virtual Reality Environment
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    Controlled Rotation of Human Observers in a Virtual Reality Environment

    Published on: April 21, 2022

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    A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
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    A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

    Published on: August 26, 2018

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    科学领域:

    • 计算机科学 计算机科学
    • 人与计算机的交互
    • 虚拟现实 虚拟现实 虚拟现实

    背景情况:

    • 在VR中的3D多对象排列需要有效的选择和操纵.
    • 现有的方法在没有控制器的交互中与封闭的,密集的对象作斗争.

    研究的目的:

    • 为虚拟现实提出一个高效,场景意识的多对象布局 (MOA) 方法.
    • 在复杂的虚拟环境中实现快速,精确和方便的对象排列.

    主要方法:

    • 开发了一个以重要性为导向的多对象初始选择算法,使用时空相关对象重要性 (IMP).
    • 实现了一个辅助结构引导的多对象操纵算法,具有多模态交互模式.

    主要成果:

    • 在复杂的,封闭的场景中,MOA显著提高了任务性能.
    • 与最先进的方法相比,减少了任务负载和提高了便利性.

    结论:

    • 拟议的MOA方法为VR中的3D多对象排列提供了一个有效的解决方案.
    • MOA增强了自然交互和用户体验,特别是在具有挑战性的虚拟环境中.