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Focus Where It Counts: A Salience-Driven Vision-Language Model for Low Vision Assistance
Jiazhao Liang, Hao Huang, Shuaihang Yuan +8
Vision-language models (VLMs) are rapidly progressing and offer promising capabilities for assistive technologies supporting persons with blindness or low vision. However, existing…
SCD4VPR: Multi-modal Scene Change Detection for Long-term Visual Place Recognition Database Update
Diwei Sheng, Vijayraj Gohil, Satyam Gaba +5
Long-term autonomy in mobile robotics requires maps that remain accurate as environments change over time. Visual Place Recognition (VPR), a core localization capability, degrades…
Evaluating OCR Performance for Assistive Technology: Effects of Walking Speed, Camera Placement, and Camera Type
Junchi Feng, Nikhil Ballem, Mahya Beheshti +5
Optical character recognition (OCR), a process that converts printed or handwritten text into machine-readable form, is widely used in assistive technology for people with blindnes…
Exploring the Use of VLMs for Navigation Assistance for People with Blindness and Low Vision
Yu Li, Yuchen Zheng, Giles Hamilton-Fletcher +6
This paper investigates the potential of vision-language models (VLMs) to assist people with blindness and low vision (pBLV) in navigation tasks. We evaluate state-of-the-art close…
Robust Computer-Vision based Construction Site Detection for Assistive-Technology Applications
Junchi Feng, Giles Hamilton-Fletcher, Nikhil Ballem +5
Purpose: Navigating urban environments poses significant challenges for individuals who are blind or have low vision, especially in areas affected by construction. Construction zon…
Can Foundation Models Reliably Identify Spatial Hazards? A Case Study on Curb Segmentation
Diwei Sheng, Giles Hamilton-Fletcher, Mahya Beheshti +2
Curbs serve as vital borders that delineate safe pedestrian zones from potential vehicular traffic hazards. Curbs also represent a primary spatial hazard during dynamic navigation…