BionicVisionXR: An Open-Source Virtual Reality Toolbox for Bionic Vision

A major outstanding challenge in the field of bionic vision is predicting what people “see” when they use their devices. The limited field of view of current devices necessitates head movements to scan the scene, which is difficult to simulate on a computer screen. In addition, many computational models of bionic vision lack biological realism.

To address these challenges, we present BionicVisionXR, an open-source virtual reality toolbox for simulated prosthetic vision that uses a psychophysically validated computational model to allow sighted participants to “see through the eyes” of a bionic eye user.

BionicVisionXR: An Open-Source Virtual Reality Toolbox for Bionic Vision
Code

Project Team

Project Lead:

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Apurv Varshney

PhD Student

Principal Investigator:

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Michael Beyeler

Associate Professor

Publications

We compare two complementary approaches to semantic preprocessing in immersive virtual reality: SemanticEdges, which highlights all relevant objects at once, and SemanticRaster, which staggers object categories over time to reduce visual clutter.

Using an immersive VR system, we systematically evaluated two behavioral tasks under four raster patterns (horizontal, vertical, checkerboard, and random) and found checkerboard raster to be the most effective.

We used a neurobiologically inspired model of simulated prosthetic vision in an immersive virtual reality environment to test the relative importance of semantic edges and relative depth cues to support the ability to avoid obstacles and identify objects.

We present VR-SPV, an open-source virtual reality toolbox for simulated prosthetic vision that uses a psychophysically validated computational model to allow sighted participants to ‘see through the eyes’ of a bionic eye user.

We propose to embed biologically realistic models of simulated prosthetic vision in immersive virtual reality so that sighted subjects can act as ‘virtual patients’ in real-world tasks.

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