skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Friday, May 16 until 2:00 AM ET on Saturday, May 17 due to maintenance. We apologize for the inconvenience.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Annotating Storefront Accessibility Data Using Crowdsourcing
The storefront accessibility can substantially impact the way people who are blind or visually impaired (BVI) travel in urban environments. Entrance localization is one of the biggest challenges to the BVI people. In addition, improperly designed staircases and obstructive store decorations can create considerable mobility challenges for BVI people, making it more difficult for them to navigate their community hence reducing their desire to travel. Unfortunately, there are few approaches to acquiring this information in advance through computational tools or services. In this paper, we propose a solution to collect large- scale accessibility data of New York City (NYC) storefronts using a crowdsourcing approach on Google Street View (GSV) panoramas. We develop a web-based crowdsourcing application, DoorFront, which enables volunteers not only to remotely label storefront accessibility data on GSV images, but also to validate the labeling result to ensure high data quality. In order to study the usability and user experience of our application, an informal beta-test is conducted and a user experience survey is designed for testing volunteers. The user feedback is very positive and indicates the high potential and usability of the proposed application.  more » « less
Award ID(s):
1827505 2131186
PAR ID:
10346688
Author(s) / Creator(s):
; ; ;
Editor(s):
Santiago, J.
Date Published:
Journal Name:
Journal on Technology & Persons with Disabilities, Scientific/Research Proceedings of 2022 CSUN Assistive Technology Conference
Volume:
10
Page Range / eLocation ID:
154-170
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, Journal on technology and persons with disabilities)
    Robles, A. (Ed.)
    Although various navigation apps are available, people who are blind or have low vision (PVIB) still face challenges to locate store entrances due to missing geospatial information in existing map services. Previously, we have developed a crowdsourcing platform to collect storefront accessibility and localization data to address the above challenges. In this paper, we have significantly improved the efficiency of data collection and user engagement in our new AI-enabled Smart DoorFront platform by designing and developing multiple important features, including a gamified credit ranking system, a volunteer contribution estimator, an AI-based pre-labeling function, and an image gallery feature. For achieving these, we integrate a specially designed deep learning model called MultiCLU into the Smart DoorFront. We also introduce an online machine learning mechanism to iteratively train the MultiCLU model, by using newly labeled storefront accessibility objects and their locations in images. Our new DoorFront platform not only significantly improves the efficiency of storefront accessibility data collection, but optimizes user experience. We have conducted interviews with six adults who are blind to better understand their daily travel challenges and their feedback indicated that the storefront accessibility data collected via the DoorFront platform would be very beneficial for them. 
    more » « less
  2. ; ; (, ACM Transactions on Accessible Computing)
    null (Ed.)
    A significant number of individuals in the United States report a disability that limits their ability to travel, including many people who are blind or visually impaired (BVI). The implications of restricted transportation result in negative impacts related to economic security, physical and mental health, and overall quality of life. Fully autonomous vehicles (FAVs) present a means to mitigate travel barriers for this population by providing new, safe, and independent travel opportunities. However, current policies governing interactions with the artificial intelligence (AI) ‘at the wheel’ of FAVs do not reflect the accessibility needs articulated by BVI people in the extant literature, failing to encourage use cases that would result in life changing mobility. By reviewing the legislative and policy efforts surrounding FAVs, we argue that the heart of this problem is due to a disjointed, laissez-faire approach to FAV accessibility that has yet to actualize the full benefits of this new transportation mode, not only for BVI people, but also for all users. We outline the necessity for a policy framework that guides the design of FAVs to include the concerns of BVI people and then propose legislative and design recommendations aimed to promote enhanced accessibility, transparency, and fairness during FAV travel. 
    more » « less
  3. ; ; ; ; ; ; ; (, Web Audio Conference WAC-2024)
    EarSketch is an online learning environment that uses the Web Audio API to teach computer science and computational thinking through music technology, production, and remixing. It is designed to broaden participation in computer science and music education for beginning learners by providing a free, web-based application coupled with curricula for informal and formal learning contexts and a library of audio content spanning multiple popular genres. This paper describes an analysis of EarSketch’s accommodations for students who are blind or visually impaired (BVI) and initial improvements to the system to improve accessibility. This paper also presents the findings of a user study designed to determine the biggest accessibility issues for EarSketch users who are BVI, and a discussion of how accessibility improvements can help broaden participation in computing and music education and, more broadly, how all web audio application developers can integrate accessibility considerations into their work. 
    more » « less
  4. (, 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops))
    null (Ed.)
    Recent work has shown that smartphone-based augmented reality technology (AR) has the potential to be leveraged by people who are blind or visually impaired (BVI) for indoor navigation. The fact that this technology is low-cost, widely available, and portable further amplifies the opportunities for impact. However, when utilizing AR for navigation, there are many possible ways to communicate the spatial information encoded in the AR world to the user, and the choice of how this information is presented to the user may have profound effects on the usability of this information for navigation. In this paper we describe frameworks from the field of spatial cognition, discuss important results in spatial cognition for folks who are BVI, and use these results and frameworks to lay out possible user interface paradigms for AR-based navigation technology for people who are BVI.We also present findings from a route dataset collected from an AR-based navigation application that support the urgency of considering spatial cognition when developing AR technology for people who are BVI. 
    more » « less
  5. ; ; ; (, Assistive Technology)
    null (Ed.)
    This paper describes the interface and testing of an indoor navigation app - ASSIST - that guides blind & visually impaired (BVI) individuals through an indoor environment with high accuracy while augmenting their understanding of the surrounding environment. ASSIST features personalized interfaces by considering the unique experiences that BVI individuals have in indoor wayfinding and offers multiple levels of multimodal feedback. After an overview of the technical approach and implementation of the first prototype of the ASSIST system, the results of two pilot studies performed with BVI individuals are presented – a performance study to collect data on mobility (walking speed, collisions, and navigation errors) while using the app, and a usability study to collect user evaluation data on the perceived helpfulness, safety, ease-of-use, and overall experience while using the app. Our studies show that ASSIST is useful in providing users with navigational guidance, improving their efficiency and (more significantly) their safety and accuracy in wayfinding indoors. Findings and user feed-back from the studies confirm some of the previous results, while also providing some new insights into the creation of such an app, including the use of customized user interfaces and expanding the types of information provided. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email