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• The Future of Urban Accessibility for People with Disabilities: Data Collection, Analytics, Policy, and Tools

  Jon E. Froehlich, Yochai Eisenberg, Maryam Hosseini, Fabio Miranda, Marc Adams, Anat Caspi, Holger Dieterich, Heather Feldner, Aldo Gonzalez, Claudina de Gyves, Joy Hammel, Reuben Kirkham, Melanie Kneisel, Delphine Labbé, Steve J. Mooney, Victor Pineda, Cláudia Fonseca Pinhão, Ana Rodríguez, Manaswi Saha, Michael Saugstad, Judy Shanley, Ather Sharif, Qing Shen, Cláudio Silva, Maarten Sukel, Eric K. Tokuda, Sebastian Felix Zappe, Anna Zivarts · 2022 · Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 22)

  This workshop paper frames urban accessibility as a "wicked problem" spanning transportation, urban planning, disability studies, public health, and human geography, and assembles a remarkably diverse team of 28 co-organizers from six countries across academia, government, NGOs,…

  urban accessibility · built environment · pedestrian infrastructure · sidewalk accessibility · data collection

• Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors

  Lida Theodorou, Daniela Massiceti, Luisa Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, Katja Hofmann · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  This paper presents a disability-first approach to constructing a machine learning dataset for teachable object recognition, developed through the ORBIT (Objects that Recognize Blind Individuals in Their environment) project. The authors argue that while AI for accessibility is…

  disability-first design · dataset creation · teachable object recognition · blind and low vision · machine learning

• Exploring Collection of Sign Language Datasets: Privacy, Participation, and Model Performance

  Danielle Bragg, Oscar Koller, Naomi Caselli, William Thies · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  This paper tackles a fundamental tension in building machine learning systems for marginalized communities: the need for large training datasets versus the privacy risks of collecting data from small, identifiable populations. The authors focus on sign language video collection,…

  sign language · privacy · machine learning · data collection · Deaf culture

• An Easy to Use Data Logger for Local User Studies

  Vagner Figueredo de Santana, Felipe Eduardo Ferreira Silva · 2019 · Proceedings of the 16th International Web for All Conference (W4A)

  This demonstration paper introduces User Test Logger, an open-source Firefox browser add-on designed to capture detailed user interaction data during local usability and accessibility studies. The authors identify a gap in available tooling: existing interaction logging tools…

  usability testing · accessibility evaluation · interaction logging · data collection · open source tools

• WeAllWalk: An Annotated Data Set of Inertial Sensor Time Series from Blind Walkers

  German H. Flores, Roberto Manduchi · 2016 · Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '16)

  This paper introduces WeAllWalk, an openly accessible and annotated data set of inertial sensor time series collected from blind individuals walking through complex indoor routes. The data set addresses a critical gap in assistive navigation research: while step counting and…

  blindness · indoor navigation · wayfinding · inertial sensing · data collection

• Supporting Orientation of People with Visual Impairment: Analysis of Large Scale Usage Data

  Hernisa Kacorri, Sergio Mascetti, Andrea Gerino, Dragan Ahmetovic, Hironobu Takagi, Chieko Asakawa · 2016 · Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '16)

  This paper analyzes large-scale remote usage data from iMove, an iOS GPS-based orientation app for people with visual impairments, to understand how users interact with assistive navigation technology in real-world conditions. Traditional assistive technology user studies are…

  visual impairment · blindness · navigation · orientation and mobility · mobile accessibility

• Accessible Motion-Capture Glove Calibration Protocol for Recording Sign Language Data from Deaf Subjects

  Pengfei Lu, Matt Huenerfauth · 2009 · Proceedings of the 11th International ACM SIGACCESS Conference on Computers and Accessibility (Assets '09)

  This paper addresses a critical bottleneck in sign language technology research: the calibration of motion-capture gloves used to record handshape data from deaf signers. Motion-capture gloves like the CyberGlove contain sensors that measure finger joint angles, but they require…

  sign language · motion capture · American Sign Language · deaf users · accessibility technology

7 results.