Collaborative Research: SaTC: CORE: Medium: Novel Algorithms and Tools for Empowering People Who Are Blind to Safeguard Private Visual Content

协作研究：SaTC：核心：媒介：帮助盲人保护私人视觉内容的新颖算法和工具

• 批准号: 2125925
• 负责人: Leah Findlater
• 金额: $ 31.64万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2125925&HistoricalAwards=false
• 关键词: Collaborative; Research; SaTC; CORE; Medium

People who are blind regularly use personal devices to take pictures and videos and share them with others. Primary reasons are to seek assistance with everyday visual tasks (e.g., recognizing objects, reading mail) and to socialize online. Regardless of the reason, they have no easy or independent means of assessing whether an image or video they are about to share inadvertently contains private information. For this project, an interdisciplinary team will design and evaluate an automated assistant that alerts users of privacy disclosures in their visual media and edits their pictures and videos to obfuscate any potential private content. If successful, these contributions will enable blind individuals for the first time to independently avoid accidental visual privacy leaks, thereby empowering them to live more independent and connected lives. This project can also be helpful to the broader population as they sometimes overlook private information in their visual content. The project team anticipates this work would generalize, with minor adaptations, to benefit other populations such as people with low vision, people with cognitive impairments, aging adults, and children. This project will involve designing novel computer vision algorithms and end-user mechanisms that empower people who are blind to independently safeguard private information in their pictures and videos. Specifically, it will consist of three key tasks: (1) creating back-end computer vision algorithms that learn to locate private content in images and videos by observing only a few examples of it (i.e., few shot semantic segmentation), (2) creating back-end computer vision algorithms that learn to locate the foreground object in images and videos (i.e., foreground object segmentation) in order to support retaining only that content, and (3) establishing effective design choices for an accessible front-end interface that engenders a level of trust that is appropriate given the algorithms' performance. The team will facilitate future extensions of this work by sharing the generated artifacts including the code for privacy-preserving algorithms, characterization of use with design recommendations for privacy-preserving technology, and a working prototype.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

盲人经常使用个人设备拍摄照片和视频并与他人分享。 主要原因是寻求日常视觉任务的帮助（例如，识别物体、阅读邮件）和在线社交。 无论出于何种原因，他们都没有简单或独立的方法来评估他们将要分享的图像或视频是否无意中包含隐私信息。 在这个项目中，一个跨学科的团队将设计和评估一个自动化助手，提醒用户在视觉媒体中的隐私泄露，并编辑他们的图片和视频，以模糊任何潜在的隐私内容。如果成功，这些贡献将使盲人首次能够独立地避免意外的视觉隐私泄露，从而使他们能够过上更加独立和相互联系的生活。这个项目也可以帮助更广泛的人群，因为他们有时会忽视他们的视觉内容中的私人信息。项目团队预计，这项工作将进行微小的调整，以使其他人群受益，如视力低下的人，认知障碍的人，老年人和儿童。 该项目将涉及设计新颖的计算机视觉算法和最终用户机制，使盲人能够独立保护其图片和视频中的私人信息。具体来说，它将包括三个关键任务：（1）创建后端计算机视觉算法，通过观察图像和视频中的几个示例来学习定位图像和视频中的隐私内容（即，少数镜头语义分割），（2）创建学习在图像和视频中定位前景对象的后端计算机视觉算法（即，前景对象分割），以便支持仅保留该内容，以及（3）为可访问的前端接口建立有效的设计选择，该前端接口产生在给定算法性能的情况下适当的信任级别。该团队将通过共享生成的工件，包括隐私保护算法的代码，隐私保护技术的设计建议的使用特征和工作原型，促进这项工作的未来扩展。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Landscape Analysis of Commercial Visual Assistance Technologies

商业视觉辅助技术的格局分析

• DOI: 10.1145/3441852.3476521
• 发表时间: 2021
• 期刊: Proceedings of the ACM ASSETS Conference
• 作者: Sadjo, Emma;Findlater, Leah;Stangl, Abigale
• 通讯作者: Stangl, Abigale

Disability-First Design and Creation of A Dataset Showing Private Visual Information Collected With People Who Are Blind

以残疾为先的设计和创建数据集，显示从盲人那里收集的私人视觉信息

• DOI: 10.1145/3544548.3580922
• 发表时间: 2023
• 期刊: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
• 作者: Sharma, Tanusree;Stangl, Abigale;Zhang, Lotus;Tseng, Yu-Yun;Xu, Inan;Findlater, Leah;Gurari, Danna;Wang, Yang
• 通讯作者: Wang, Yang

ImageAlly: A Human-AI Hybrid Approach to Support Blind People in Detecting and Redacting Private Image Content

ImageAlly：一种支持盲人检测和编辑私人图像内容的人机人工智能混合方法

• 发表时间: 2023
• 期刊: The Symposium on Usable Privacy and Security (SOUPS
• 作者: Zhang, Zhuohao Jerry;Kaushik, Smirity;Seo, JooYoung;Yuan, Haolin;Das, Sauvik;Findlater, Leah;Gurari, Danna;Stangl, Abigale;Wang, Yang
• 通讯作者: Wang, Yang

“Dump it, Destroy it, Send it to Data Heaven”: Blind People’s Expectations for Visual Privacy in Visual Assistance Technologies

“转储它、销毁它、将其发送到数据天堂”：盲人对视觉辅助技术中视觉隐私的期望

• DOI: 10.1145/3587281.3587296
• 发表时间: 2023
• 期刊: Send it to Data Heaven”: Blind People’s Expectations for Visual Privacy in Visual Assistance Technologies
• 作者: Stangl, Abigale;Sadjo, Emma;Emami-Naeini, Pardis;Wang, Yang;Gurari, Danna;Findlater, Leah
• 通讯作者: Findlater, Leah

Privacy Concerns for Visual Assistance Technologies

视觉辅助技术的隐私问题

• DOI: 10.1145/3517384
• 发表时间: 2022
• 期刊: ACM Transactions on Accessible Computing
• 影响因子: 2.4
• 作者: Stangl, Abigale;Shiroma, Kristina;Davis, Nathan;Xie, Bo;Fleischmann, Kenneth R.;Findlater, Leah;Gurari, Danna
• 通讯作者: Gurari, Danna