Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Depth Perception and Spatial Vision01:15

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.

You might also read

Related Articles

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

Sort by
Same author

Diving Deep Into Time: Temporal Arrangements for Embedded Visualization in Swimming Videos.

IEEE transactions on visualization and computer graphics·2026
Same author

Design guidelines for animated data visualization based on perceptual capacity limits.

Cognitive research: principles and implications·2026
Same author

Investigating the Effects of Augmented Reality on Message Credibility When Visualizing Environmental Impacts.

IEEE transactions on visualization and computer graphics·2025
Same author

Reframing Pattern: A Comprehensive Approach to a Composite Visual Variable.

IEEE transactions on visualization and computer graphics·2025
Same author

Beyond Log Scales: Toward Cognitively Informed Bar Charts for Orders of Magnitude Values.

IEEE transactions on visualization and computer graphics·2025
Same author

An Autoethnography on Visualization Literacy: A Wicked Measurement Problem.

IEEE transactions on visualization and computer graphics·2025
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
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
See all related articles

Related Experiment Video

Updated: May 7, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
13:01

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Hybrid-image visualization for large viewing environments.

Petra Isenberg1, Pierre Dragicevic, Wesley Willett

  • 1INRIA.

IEEE Transactions on Visualization and Computer Graphics
|September 21, 2013
PubMed
Summary
This summary is machine-generated.

Hybrid-image visualization blends two views into one static image for large displays. This technique enhances data analysis by allowing viewers at different distances to see distinct information without tracking.

More Related Videos

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

Related Experiment Videos

Last Updated: May 7, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
13:01

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Published on: February 8, 2014

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

Area of Science:

  • Computer Graphics
  • Human-Computer Interaction
  • Information Visualization

Background:

  • Large-scale displays enable multiple users to view data simultaneously from varying distances.
  • Traditional visualizations struggle to cater to both overview and detail-in-context tasks for diverse viewing distances.
  • There is a need for static visualization techniques that adapt to different viewing distances without user tracking.

Purpose of the Study:

  • To introduce and investigate hybrid-image visualization for data analysis in large-scale viewing environments.
  • To enable simultaneous perception of two distinct visual representations within a single static view.
  • To support both overview tasks from afar and detail-in-context tasks up close.

Main Methods:

  • Developed a perception-based blending approach to combine two visualizations into one hybrid image.
  • Defined a design space for creating hybrid-image visualizations.
  • Explored the perceptual rationale behind the effectiveness of hybrid-image visualizations.

Main Results:

  • Demonstrated that hybrid-image visualizations can present two full-screen visualizations in a single static view.
  • Showcased how different visual representations are perceived at different viewing distances.
  • Provided examples and introduced tools to facilitate the design of hybrid-image visualizations.

Conclusions:

  • Hybrid-image visualization is a novel technique for enhancing data analysis on large displays.
  • This approach effectively supports multiple users with different information needs based on their viewing distance.
  • The presented methods and tools aid in the creation and application of hybrid-image visualizations for large-scale data analysis.