EnVisionVR: A Scene Interpretation Tool for Visual Accessibility in Virtual Reality
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866929700148871168 |
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| author | Chen, Junlong Esparza, Rosella P. Galindo Garaj, Vanja Kristensson, Per Ola Dudley, John |
| author_facet | Chen, Junlong Esparza, Rosella P. Galindo Garaj, Vanja Kristensson, Per Ola Dudley, John |
| contents | Effective visual accessibility in Virtual Reality (VR) is crucial for Blind and Low Vision (BLV) users. However, designing visual accessibility systems is challenging due to the complexity of 3D VR environments and the need for techniques that can be easily retrofitted into existing applications. While prior work has studied how to enhance or translate visual information, the advancement of Vision Language Models (VLMs) provides an exciting opportunity to advance the scene interpretation capability of current systems. This paper presents EnVisionVR, an accessibility tool for VR scene interpretation. Through a formative study of usability barriers, we confirmed the lack of visual accessibility features as a key barrier for BLV users of VR content and applications. In response, we designed and developed EnVisionVR, a novel visual accessibility system leveraging a VLM, voice input and multimodal feedback for scene interpretation and virtual object interaction in VR. An evaluation with 12 BLV users demonstrated that EnVisionVR significantly improved their ability to locate virtual objects, effectively supporting scene understanding and object interaction. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_03564 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | EnVisionVR: A Scene Interpretation Tool for Visual Accessibility in Virtual Reality Chen, Junlong Esparza, Rosella P. Galindo Garaj, Vanja Kristensson, Per Ola Dudley, John Human-Computer Interaction Effective visual accessibility in Virtual Reality (VR) is crucial for Blind and Low Vision (BLV) users. However, designing visual accessibility systems is challenging due to the complexity of 3D VR environments and the need for techniques that can be easily retrofitted into existing applications. While prior work has studied how to enhance or translate visual information, the advancement of Vision Language Models (VLMs) provides an exciting opportunity to advance the scene interpretation capability of current systems. This paper presents EnVisionVR, an accessibility tool for VR scene interpretation. Through a formative study of usability barriers, we confirmed the lack of visual accessibility features as a key barrier for BLV users of VR content and applications. In response, we designed and developed EnVisionVR, a novel visual accessibility system leveraging a VLM, voice input and multimodal feedback for scene interpretation and virtual object interaction in VR. An evaluation with 12 BLV users demonstrated that EnVisionVR significantly improved their ability to locate virtual objects, effectively supporting scene understanding and object interaction. |
| title | EnVisionVR: A Scene Interpretation Tool for Visual Accessibility in Virtual Reality |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2502.03564 |