Identifying Crucial Objects in Blind and Low-Vision Individuals' Navigation

TL;DR

This paper identifies 90 crucial objects for blind and low-vision navigation, analyzes their presence in datasets, and provides detailed labels to improve navigation aids for the BLV community.

Contribution

It creates a comprehensive list of essential objects for BLV navigation, validated through videos and focus groups, addressing gaps in existing datasets.

Findings

Most datasets contain only a small subset of these objects.

The object list and labels are publicly available for research.

Analysis highlights gaps in current computer vision training data.

Abstract

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.