1. Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development
- Author
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Giles Hamilton-Fletcher, Mingxin Liu, Diwei Sheng, Chen Feng, Todd E. Hudson, John-Ross Rizzo, and Kevin C. Chan
- Subjects
Assistive technology ,sensory substitution ,blindness ,low vision ,navigation ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Medical technology ,R855-855.5 - Abstract
Goal: Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. Methods: We tested five smartphone-based distance-estimation approaches in the image center and periphery at 1–3 meters, including machine learning (CoreML), infrared grid distortion (IR_self), light detection and ranging (LiDAR_back), and augmented reality room-tracking on the front (ARKit_self) and back-facing cameras (ARKit_back). Results: For accuracy in the image center, all approaches had Conclusions: We provide key information that helps design reliable smartphone-based visual assistive technologies to enhance the functionality of PBLV.
- Published
- 2024
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