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.
Visual System01:26

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

You might also read

Related Articles

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

Sort by
Same author

Semantic Scene Graphs for Creating a Localization-Ready Internet of Things.

IEEE transactions on visualization and computer graphics·2026
Same author

Ambient Analytics: Calm Technology for Immersive Visualization and Sensemaking.

IEEE computer graphics and applications·2026
Same author

Hybrid User Interfaces: Past, Present, and Future of Complementary Cross-Device Interaction in Mixed Reality.

IEEE transactions on visualization and computer graphics·2026
Same author

HandLight: Light Estimation from Hand Interaction in Mixed Reality.

IEEE transactions on visualization and computer graphics·2026
Same author

Situated Brushing and Linking in Virtual and Augmented Reality.

IEEE transactions on visualization and computer graphics·2026
Same author

See what I Mean? Mobile Eye-Perspective Rendering for Optical See-Through Head-Mounted Displays.

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: Jun 26, 2026

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

Comprehensible visualization for augmented reality.

Denis Kalkofen1, Erick Mendez, Dieter Schmalstieg

  • 1Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria. kalkofen@icg.tugraz.at

IEEE Transactions on Visualization and Computer Graphics
|January 17, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces interactive visualizations for Augmented Reality (AR) to improve understanding of spatial relationships. Focus and Context (F+C) techniques enhance perception in complex environments.

More Related Videos

Combining Augmented Reality and 3D Printing to Display Patient Models on a Smartphone
09:26

Combining Augmented Reality and 3D Printing to Display Patient Models on a Smartphone

Published on: January 2, 2020

Related Experiment Videos

Last Updated: Jun 26, 2026

Photorealistic Learned Landscapes for Augmented Reality
06:54

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

Combining Augmented Reality and 3D Printing to Display Patient Models on a Smartphone
09:26

Combining Augmented Reality and 3D Printing to Display Patient Models on a Smartphone

Published on: January 2, 2020

Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Virtual Reality

Background:

  • Augmented Reality (AR) applications require clear spatial understanding between virtual and real objects.
  • Existing visualization techniques may not adequately convey spatial relationships in AR.

Purpose of the Study:

  • To present and evaluate interactive visualization techniques for enhancing spatial comprehension in AR.
  • To explore the effectiveness of Focus and Context (F+C) visualizations for AR applications.

Main Methods:

  • Discussed visualization techniques and their suitability for AR.
  • Applied F+C visualizations in various AR scenarios (e.g., X-Ray vision, attention guidance).
  • Developed cascaded and multi-level F+C visualizations for cluttered scenes and interactive control tools.

Main Results:

  • Demonstrated F+C visualizations' ability to influence perception of hidden/nearby objects.
  • Showcased interactive filters and tools for controlling augmentation levels.
  • Compared context-preserving vs. uniform enhancement for real-world imagery augmentation.

Conclusions:

  • Interactive visualizations, particularly F+C, significantly improve spatial relationship comprehension in AR.
  • Cascaded and multi-level F+C visualizations effectively handle complex environments.
  • Context-preserving enhancements are valuable for AR imagery.