PFI:AIR-TT: Video Collaboratory: A Platform for Active Viewing and Collaboration with Video Data

PFI:AIR-TT：视频协作：主动查看视频数据并进行协作的平台

• 批准号: 1500195
• 负责人: David Wilson
• 金额: $ 19.99万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1500195&HistoricalAwards=false
• 关键词: PFI; AIR; TT; Video; Collaboratory

This PFI: AIR Technology Translation project focuses on translating an online software technology (The Video Collaboratory) to fill the need for innovative support in small group collaboration and discussion around video documents. The Video Collaboratory is important because increasingly huge amounts of video are being generated for business and personal use. And while there are currently ways to distribute / watch video, it is still not easy to drill into, analyze, and note important details from within the video as a means to an end, particularly when working with others. From corporate training to healthcare, education, and security, people need effective ways to privately converse about, mark up and brainstorm around videos that are linked directly into the video content itself. The project will result in a scaled-up and enhanced Video Collaboratory platform with the following unique features: new ways for precision interaction with video documents, direct connection of group discussions to the video timeline, and private social networking to support meaningful work with videos. These features provide the following advantages: enabling clearer, deeper discussion; reducing error and confusion; and increasing efficiency / saving time when compared to the leading competing technologies in this market space, such as YouTube and Vimeo, that focus on distribution rather than detailed analysis and use of video documents. This project will develop a market-ready technology platform for next-generation collaboration around video data.This project addresses the following technology gaps as it translates from research discovery toward commercial application: (1) social presence affordances and group analytics to enable group-guided viewing and synchronous interaction around video documents; (2) rich communication pathways to support multimedia annotations and video-centric filtering of commentary as part of video-anchored discussion; (3) responsive components for interface and video data to scale across platforms (particularly mobile) with smart video streaming that adapts to user network environments; and (4) elastic, scalable, and socially-aware metrics for group/project organization, access/privacy control, and content management for sharing. Significant contributions to the research and knowledge base are novel techniques designed to address these gaps, validated through user study testing. Contributions include techniques for synchronous interaction around video documents; social discussion threading (integrating context from annotated video segmentation, user interaction analytics, and discussion content); weighted adaptive video streaming to prioritize transfer of content by discussion activity; and a flexible, socially-aware model for access management and content sharing. In addition, personnel involved in this project, graduate students and post-docs, will receive technology translation and entrepreneurship experiences through research development and discovery toward commercial reality.

该PFI：空气技术翻译项目的重点是翻译在线软件技术（视频协作），以满足小组协作和围绕视频文档讨论的创新支持的需求。视频协作非常重要，因为正在为业务和个人使用而生成越来越多的视频。尽管当前有分发 /观看视频的方法，但仍不容易钻取，分析和记录视频中的重要细节，以作为结束的手段，尤其是在与他人合作时。从公司培训到医疗保健，教育和安全，人们需要有效的方法来私下交谈，标记和集思广益，并在视频本身直接链接到视频本身。该项目将带来一个扩展和增强的视频协作平台，具有以下独特功能：与视频文档进行精确互动的新方法，将小组讨论直接连接到视频时间表以及私人社交网络，以支持与视频的有意义的工作。这些功能提供了以下优势：实现更清晰，更深入的讨论；减少错误和混乱；与该市场领域的领先竞争技术（例如YouTube和Vimeo）相比，增加效率 /节省时间，该技术专注于分发而不是详细的分析和视频文档的使用。该项目将开发一个可围绕视频数据的下一代合作的市场就绪技术平台。该项目解决了以下技术差距，因为它从研究发现转化为商业应用程序：（1）社交形象和小组分析以启用围绕视频文档的团体指导观看和同步互动； （2）作为视频锚定讨论的一部分，支持多媒体注释和以视频为中心的评论过滤的丰富沟通途径； （3）接口和视频数据的响应敏感组件，以跨平台（尤其是移动设备）进行扩展，并具有适应用户网络环境的智能视频流； （4）组/项目组织，访问/隐私控制以及共享内容管理的弹性，可扩展性和社会意识的指标。对研究和知识库的重大贡献是旨在解决这些差距的新技术，通过用户研究测试验证了这些差距。贡献包括围绕视频文档同步互动的技术；社交讨论线程（从注释的视频细分，用户互动分析和讨论内容中整合上下文）；加权自适应视频流以讨论活动的优先级转移内容；以及一个灵活的，具有社会意识的模型，用于访问管理和内容共享。此外，参与该项目的人员，研究生和博士后，将通过研究开发和发现对商业现实进行技术翻译和企业家精神体验。