A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals’ Navigation

AmazUtah_NLP at SemEval-2024 Task 9: A MultiChoice Question Answering System for Commonsense Defying Reasoning


[Submitted on 23 Jul 2024]

View a PDF of the paper titled A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals’ Navigation, by Md Touhidul Islam and 4 other authors

View PDF

Abstract:This paper introduces a dataset for improving real-time object recognition systems to aid blind and low-vision (BLV) individuals in navigation tasks. The dataset comprises 21 videos of BLV individuals navigating outdoor spaces, and a taxonomy of 90 objects crucial for BLV navigation, refined through a focus group study. We also provide object labeling for the 90 objects across 31 video segments created from the 21 videos. A deeper analysis reveals that most contemporary datasets used in training computer vision models contain only a small subset of the taxonomy in our dataset. Preliminary evaluation of state-of-the-art computer vision models on our dataset highlights shortcomings in accurately detecting key objects relevant to BLV navigation, emphasizing the need for specialized datasets. We make our dataset publicly available, offering valuable resources for developing more inclusive navigation systems for BLV individuals.

Submission history

From: Md Touhidul Islam [view email]
[v1]
Tue, 23 Jul 2024 18:19:27 UTC (24,239 KB)



Source link
lol

By stp2y

Leave a Reply

Your email address will not be published. Required fields are marked *

No widgets found. Go to Widget page and add the widget in Offcanvas Sidebar Widget Area.