Real-Time Object Detection and Augmented Reality to Support Low-Vision Navigation and Object Localization : A Demonstration

Low-vision (LV) people often face difficulties in navigating complex environments and recognizing objects due to reduced visual acuity, contrast sensitivity, or field of view. In this paper, we present a prototype that combines real-time object detection with augmented reality (AR) visualization to enhance spatial awareness for LV users, supporting safe navigation and object localization in indoor spaces. The system integrates an RGB-D camera and a Microsoft HoloLens 2 headset via ROS and Unity, using a YOLOv11-based perception pipeline to detect and localize static and dynamic objects in 3D and display high-contrast AR icons above the detected objects within the user’s field of view, conveying both their position and identity.

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Publication Details

Journal
KOPS (University of Konstanz)
Published
2026-03-20
DOI
https://doi.org/10.48787/kops/352-2-1iibq6fnnc4p43
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
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article

Real-Time Object Detection and Augmented Reality to Support Low-Vision Navigation and Object Localization : A Demonstration

Nicolas Ruffieux, Denis Lalanne, Karim Aebischer, Yong-Joon Thoo
KOPS (University of Konstanz)
Augmented Reality Applications
article

Real-Time Object Detection and Augmented Reality to Support Low-Vision Navigation and Object Localization : A Demonstration

Nicolas Ruffieux, Denis Lalanne, Karim Aebischer, Yong-Joon Thoo
article en

Abstract

Low-vision (LV) people often face difficulties in navigating complex environments and recognizing objects due to reduced visual acuity, contrast sensitivity, or field of view. In this paper, we present a prototype that combines real-time object detection with augmented reality (AR) visualization to enhance spatial awareness for LV users, supporting safe navigation and object localization in indoor spaces. The system integrates an RGB-D camera and a Microsoft HoloLens 2 headset via ROS and Unity, using a YOLOv11-based perception pipeline to detect and localize static and dynamic objects in 3D and display high-contrast AR icons above the detected objects within the user’s field of view, conveying both their position and identity.

KOPS (University of Konstanz)
University of Fribourg (CH)
Openalex Percentile: Top 9%
Augmented Reality Applications
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