Identifying Crucial Objects in Blind and Low-Vision Individuals' Navigation
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909294219231232 |
|---|---|
| author | Islam, Md Touhidul Kabir, Imran Pearce, Elena Ariel Reza, Md Alimoor Billah, Syed Masum |
| author_facet | Islam, Md Touhidul Kabir, Imran Pearce, Elena Ariel Reza, Md Alimoor Billah, Syed Masum |
| contents | This paper presents a curated list of 90 objects essential for the navigation of blind and low-vision (BLV) individuals, encompassing road, sidewalk, and indoor environments. We develop the initial list by analyzing 21 publicly available videos featuring BLV individuals navigating various settings. Then, we refine the list through feedback from a focus group study involving blind, low-vision, and sighted companions of BLV individuals. A subsequent analysis reveals that most contemporary datasets used to train recent computer vision models contain only a small subset of the objects in our proposed list. Furthermore, we provide detailed object labeling for these 90 objects across 31 video segments derived from the original 21 videos. Finally, we make the object list, the 21 videos, and object labeling in the 31 video segments publicly available. This paper aims to fill the existing gap and foster the development of more inclusive and effective navigation aids for the BLV community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_13175 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Identifying Crucial Objects in Blind and Low-Vision Individuals' Navigation Islam, Md Touhidul Kabir, Imran Pearce, Elena Ariel Reza, Md Alimoor Billah, Syed Masum Computer Vision and Pattern Recognition This paper presents a curated list of 90 objects essential for the navigation of blind and low-vision (BLV) individuals, encompassing road, sidewalk, and indoor environments. We develop the initial list by analyzing 21 publicly available videos featuring BLV individuals navigating various settings. Then, we refine the list through feedback from a focus group study involving blind, low-vision, and sighted companions of BLV individuals. A subsequent analysis reveals that most contemporary datasets used to train recent computer vision models contain only a small subset of the objects in our proposed list. Furthermore, we provide detailed object labeling for these 90 objects across 31 video segments derived from the original 21 videos. Finally, we make the object list, the 21 videos, and object labeling in the 31 video segments publicly available. This paper aims to fill the existing gap and foster the development of more inclusive and effective navigation aids for the BLV community. |
| title | Identifying Crucial Objects in Blind and Low-Vision Individuals' Navigation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2408.13175 |