II-EN: Infrastructure for Gesture Interface Research Outside the Lab

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。拟议的工作重点是手势人机界面，为严重身体残疾的个人提供基于相机的界面，通过手语和手势进行交流，和/或人体和手的运动。拟议的基础设施改进将使在实验室外进行基于视频的研究成为可能，也是可行的。基础设施包括一个坚固耐用的移动的系统，用于现场捕获同步的多视图数字视频，例如在聋人学校和残疾人家中。软件基础设施将得到加强，以支持开发界面，用于部署将在外地使用的系统，并对在外地收集的视频进行注释。从更大和更多样化的对象库中采集视频数据将导致收集更多样化的视频，用于语言差异研究和计算机视觉算法的培训和测试，作为该项目的一部分开发的基于摄像机的辅助技术将对严重身体残疾的成人和儿童及其朋友、家人和照顾者的生活质量产生积极影响;该软件将在特殊护理设施中分发，也将通过免费下载在互联网上提供。在这个项目中开发的自动手势定位，索引，匹配和检索方法将使手语文学，传说，诗歌，表演，课程，从数字视频图书馆和DVD的基于符号的搜索。这种能力可能对改善聋人的教育、机会和机会产生深远的影响。在这个项目中开发的手势分析，匹配和检索方法也应该加速对手语和口语手势成分的语言和跨语言研究。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The proposed work is focused on gestural human computer interfaces, camera-based interfaces for individuals with severe physical disabilities, communication through sign language and gesture, and/or motion of the human body and hands. The proposed infrastructure enhancement would make it possible, as well as practical, to conduct video-based research outside the lab. The infrastructure includes a ruggedized mobile system for capture of synchronized, multi-view digital video on site, for instance in schools for the Deaf and in homes for the disabled. Software infrastructure will be enhanced to support the development of the interface for deployment of the systems to be used in the field, and for annotation of video collected in the field. Video data capture from a larger and more diverse pool of subjects will lead to a more diverse collection of videos for study of linguistic variation and for training and testing of computer vision algorithms.The camera-based assistive technology developed as part of this project will have a positive impact on the quality of life of adults and children with severe physical disabilities, as well as their friends, families and caregivers; the software will be disseminated at special care facilities and will also be available on the internet via free download. The automated gesture spotting, indexing, matching, and retrieval methods developed in this project would enable sign-based search of ASL literature, lore, poems, performances, courses, from digital video libraries and DVDs. Such capability could have far-reaching implications for improving education, opportunities, and access for the deaf. The gestural analysis, matching, and retrieval methods developed in this project should also accelerate linguistic and cross-linguistic research on signed languages and the gestural components of spoken languages.