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• Active Learning for Web Accessibility Evaluation

  Mengni Zhang, Can Wang, Zhi Yu, Chao Shen, Jiajun Bu · 2017 · Proceedings of the 14th International Web for All Conference (W4A)

  This paper introduces "active-prediction," a semi-supervised machine learning method that addresses a fundamental bottleneck in web accessibility evaluation: the prohibitive cost of evaluating all pages in a large website. Current practice relies on sampling methods (ad hoc,…

  accessibility evaluation · machine learning · active learning · web accessibility · automated testing

• WAEM: A Web Accessibility Evaluation Metric Based on Partial User Experience Order

  Shuyi Song, Can Wang, Liangcheng Li, Zhi Yu, Xiao Lin, Jiajun Bu · 2017 · Proceedings of the 14th International Web for All Conference (W4A)

  This paper introduces WAEM (Web Accessibility Experience Metric), a novel accessibility metric that derives checkpoint weights from actual user experience data rather than from WCAG priority levels. The authors demonstrate that existing metrics like WAB and WAQM, which weight…

  accessibility metrics · user experience · accessibility evaluation · machine learning · SVM

• A Task Assignment Strategy for Crowdsourcing-Based Web Accessibility Evaluation System

  Liangcheng Li, Can Wang, Shuyi Song, Zhi Yu, Fenqin Zhou, Jiajun Bu · 2017 · Proceedings of the 14th International Web for All Conference (W4A)

  This paper addresses a practical challenge in scaling web accessibility evaluation: how to effectively assign manual evaluation tasks to volunteer crowdsource workers with varying levels of expertise. While automated tools can check many accessibility checkpoints, they cannot…

  web accessibility evaluation · crowdsourcing · machine learning · automated testing · conformance testing

• Real-Time Depth-Camera Based Hand Tracking for ASL Recognition

  Brandon Taylor, Anind Dey, Daniel Siewiorek, Asim Smailagic · 2017 · Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This demonstration paper validates the use of a publicly available real-time hand tracking algorithm (Sphere-Mesh) for recognizing American Sign Language (ASL) handshapes using a depth camera. Sign Language Recognition (SLR) has long been a motivating goal for high-precision…

  sign language recognition · hand tracking · computer vision · depth camera · machine learning

• Speed-Accuracy Tradeoffs for Detecting Sign Language Content in Video Sharing Sites

  Frank M. Shipman, Satyakiran Duggina, Caio D.D. Monteiro, Ricardo Gutierrez-Osuna · 2017 · Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)

  This paper addresses the problem of automatically detecting sign language content in videos on sharing platforms like YouTube and Vimeo. For many deaf and hard-of-hearing people, sign language is their primary communication medium, and they rely on online video content to stay…

  sign language · computer vision · video classification · information retrieval · deaf and hard of hearing

• "Hands On" Visual Recognition for Visually Impaired Users

  Joan Sosa-García, Francesca Odone · 2017 · ACM Transactions on Accessible Computing

  This paper presents a collaborative visual recognition system designed to help blind or visually impaired (BVI) users identify specific product instances — distinguishing between brands, models, or types of objects that feel similar when handled. While BVI individuals can often…

  visual impairment · object recognition · computer vision · assistive technology · wearable technology

• People with Visual Impairment Training Personal Object Recognizers: Feasibility and Challenges

  Hernisa Kacorri, Kris M. Kitani, Jeffrey P. Bigham, Chieko Asakawa · 2017 · CHI Conference on Human Factors in Computing Systems

  This paper explores whether people with visual impairments can train their own personalized object recognition systems using a smartphone camera and a small number of example photos. The authors address a fundamental limitation of existing object recognition tools for blind…

  object recognition · computer vision · blindness · transfer learning · personalization

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