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Related Experiment Video

Updated: Jul 13, 2026

Photorealistic Learned Landscapes for Augmented Reality

Photorealistic Learned Landscapes for Augmented Reality

Published on: June 27, 2025

Development of an augmented virtuality framework using user-defined passthrough surfaces.

Abdul Hannan Bin Zulkarnain¹, Attila Gere¹

¹Department of Postharvest, Supply Chain, Commerce and Sensory Science, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences, Villányi út 29-31, Budapest, H-1118, Hungary.

|July 12, 2026

Summary

This study introduces an augmented virtuality framework controlling real-world visibility through virtual apertures. This enables controlled product interaction and training in mixed reality environments.

Keywords:

Mixed reality OpenXR Passthrough Unity Virtual reality

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Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

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Photorealistic Learned Landscapes for Augmented Reality

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Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

Area of Science:

Computer Science
Human-Computer Interaction
Virtual Reality

Background:

Augmented reality (AR) and virtual reality (VR) systems often present fully virtual or augmented environments.
Controlling the visibility of the physical world within mixed reality (MR) is crucial for specific applications like sensory studies and training.

Purpose of the Study:

To present a novel augmented virtuality (AV) framework that precisely controls the user's view of the physical scene.
To enable controlled interaction with real-world objects within a virtual context for research and training.

Main Methods:

Developed an AV framework using surface-projected, overlay-style compositing.
Implemented developer-defined geometric apertures (circular or square) to admit physical scene data.
Ensured stable alignment between virtual geometry and the physical workspace using standard extended reality (XR) configuration.

Main Results:

Achieved deterministic compositing, binding real imagery to user-defined meshes and preventing visual leakage outside defined apertures.
Demonstrated stable alignment of virtual and physical elements during head motion.
Showcased framework flexibility supporting various aperture shapes and optional 3D environments without altering core projection logic.

Conclusions:

The presented AV framework offers precise control over real-world visibility within mixed reality.
This technology is suitable for sensory and consumer studies, training, human factors research, and rehabilitation requiring constrained real-world interaction.