Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Depth Perception and Spatial Vision

Depth Perception and Spatial Vision

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.

Virtual Work for a System of Connected Rigid Bodies

Virtual Work for a System of Connected Rigid Bodies

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,...

Gestalt Principles of Perception

Gestalt Principles of Perception

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

The genetic control of growth rate: a systems biology study in yeast.

BMC systems biology·2012

Same author

Presence of somatic mutations in most early-stage pancreatic intraepithelial neoplasia.

Gastroenterology·2012

Same author

Terpenoids from root bark of Celastrus orbiculatus.

Phytochemistry·2011

Same author

Zero-order noise suppression with various space-shifting manipulations of reconstructed images in digital holography.

Applied optics·2011

Same author

Design, synthesis and insecticidal activities of novel pyrazole amides containing hydrazone substructures.

Pest management science·2011

Same author

Imbricate scales as a design construct for microsystem technologies.

Small (Weinheim an der Bergstrasse, Germany)·2011

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

Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026

Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026

Same journal

Spatial-temporal Relation guided Motion Transfer via Diffusion Model.

IEEE transactions on visualization and computer graphics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 10, 2026

Controlled Rotation of Human Observers in a Virtual Reality Environment

Controlled Rotation of Human Observers in a Virtual Reality Environment

Published on: April 21, 2022

MOA: Efficient Scene-Aware Multi-Object Arrangement in VR.

Xuehuai Shi, Yuhan Duan, Ziteng Wang

IEEE Transactions on Visualization and Computer Graphics

|November 24, 2025

Summary

This summary is machine-generated.

This study introduces an efficient method for 3D multi-object arrangement in virtual reality, improving selection and manipulation in complex, occluded scenes. The new approach enhances task efficiency and user experience in virtual environments.

More Related Videos

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

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

Published on: August 26, 2018

Photorealistic Learned Landscapes for Augmented Reality

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

Related Experiment Videos

Last Updated: Jan 10, 2026

Controlled Rotation of Human Observers in a Virtual Reality Environment

Controlled Rotation of Human Observers in a Virtual Reality Environment

Published on: April 21, 2022

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

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

Published on: August 26, 2018

Photorealistic Learned Landscapes for Augmented Reality

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

Area of Science:

Computer Science
Human-Computer Interaction
Virtual Reality

Background:

3D multi-object arrangement in VR requires efficient selection and manipulation.
Existing methods struggle with occluded, densely packed objects in controller-free interactions.

Purpose of the Study:

To propose an efficient, scene-aware multi-object arrangement (MOA) method for VR.
To enable fast, precise, and convenient object arrangement in complex virtual environments.

Main Methods:

Developed an importance-driven multi-object initial selection algorithm using spatiotemporally correlated object importance (IMP).
Implemented an auxiliary-structure guided multi-object manipulation algorithm with a multi-modal interaction mode.

Main Results:

MOA significantly improves task performance in complex, occluded scenes.
Reduced task load and enhanced convenience compared to state-of-the-art methods.

Conclusions:

The proposed MOA method offers an efficient solution for 3D multi-object arrangement in VR.
MOA enhances natural interaction and user experience, particularly in challenging virtual environments.