Automated Tactilization of Graphical Images: Full Access to Math, Science, and Engineering for Blind Students

图形图像的自动触觉化：盲人学生全面接触数学、科学和工程

• 批准号: 0415273
• 负责人: Richard Ladner
• 金额: --
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-15 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0415273&HistoricalAwards=false
• 关键词: Automated; Tactilization; Graphical; Images; Full

Graphical images (line graphs, bar charts, diagrams, illustrations, etc.) are prevalent in math, science, and engineering (MSE) textbooks at all educational levels. But while studies have shown that tactual perception is the best modality for comprehension of graphical images by people who are visually impaired, the graphical images found in textbooks typically aren't available in this format. Visually impaired students' lack of full access to the contents of textbooks impedes their learning, development, and success in MSE careers, areas in which individuals with disabilities are underrepresented. This project seeks to address this problem, by developing innovative ways to overcome obstacles to the timely translation of graphical images into a tactual format. The needs of two user communities will be addressed: transcribers who translate graphical images into tactual formats within low- and high-production environments; and students who are in MSE classes at the K-12 and postsecondary education levels, are blind, and read Braille. To these ends, the PI has assembled an interdisciplinary team with expertise in image processing, machine learning, IR, HCI, experiment design, and addressing the needs of students with disabilities. The PI and his team will design and develop the Tactile Graphics Assistant (TG Assistant), a set of plug-ins for Adobe Photoshop and Illustrator, which will support transcribers in transforming, as automatically and intelligently as possible, graphical images into a high-quality tactual form that can be reproduced and then used by students who are blind. Empirical studies will be conducted to better understand the perception of tactile graphics, and to inform the design of prediction models to estimate image comprehension time and comprehension accuracy, the application of machine learning techniques to classify images by their type, and the design of image processing algorithms to carry out the steps (appropriate for the image type) to translate an image into a tactual form. A user-centered design approach will be followed during the development of the TG Assistant. Project benefits will be documented by three proof-of-concept activities, wherein the TG Assistant will be used to provide access to textbook images to three students at the K-8, high school, and postsecondary education levels. Broader Impact. Tactual access to graphical images will improve blind students' learning, performance, retention, and potential to succeed in MSE careers. Project outcomes will include invaluable data on the tactual perception of tactile graphics, new image processing and classification algorithms, and a usable tool to streamline the translation of graphical images into a tactual format. Research findings on the translation of graphical images will be summarized as a set of guidelines and distributed to transcribers. The PI will make an effort to incorporate the guidelines and TG Assistant into transcriber training programs. The research team includes individuals from under-represented groups (women, minority, and disabled individuals.

图形图像（线图，条形图，图表，插图等）在所有教育水平上都普遍存在数学，科学和工程（MSE）教科书。 但是，尽管研究表明，触发感是理解视力障碍的人理解图形图像的最佳方式，但教科书中发现的图形图像通常在这种格式中不可用。 视力障碍学生无法完全访问教科书内容，这阻碍了他们在MSE职业中的学习，发展和成功，这些领域是残疾人人数不足的领域。 该项目试图通过开发创新的方法来克服障碍，以及时将图形图像转换为触觉格式，以解决这个问题。 将解决两个用户社区的需求：在低生产环境中将图形图像转换为触觉格式的转录者；在K-12和高等教育水平的MSE课程的学生是盲目的，并且阅读盲文。 对于这些目的，PI汇集了一个跨学科团队，具有图像处理，机器学习，IR，HCI，实验设计方面的专业知识，并满足了残疾学生的需求。 PI和他的团队将设计和开发触觉图形助理（TG Assistant），这是Adobe Photoshop和Illustrator的一组插件，该插件将在尽可能自动，智能上的转换中支持转换者，将图形图像转换为可以复制的高质量触觉形式，并由失明的学生使用。 将进行经验研究，以更好地理解触觉图形的感知，并为预测模型的设计提供信息，以估算图像理解时间和理解精度，使用机器学习技术通过其类型对图像进行分类以及图像处理算法的设计，以及将图像处理（适用于图像类型）以将图像转化为触觉形式。 在TG助手的开发期间，将采用以用户为中心的设计方法。 项目益处将通过三项概念验证活动记录，其中TG助手将用于为K-8，高中和专上教育水平的三个学生提供教科书图像的访问。 更广泛的影响。触发图形图像将改善盲人学生的学习，表现，保留和在MSE职业中取得成功的潜力。 项目成果将包括有关触觉图形触觉感知的宝贵数据，新的图像处理和分类算法，以及简化图形图像转换为触觉格式的可用工具。 关于图像图像翻译的研究结果将以一组准则进行总结，并分配给转录器。 PI将努力将指南和TG助手纳入跨柜员培训计划。 研究小组包括来自代表性不足的群体（妇女，少数群体和残疾人的人）。