SBIR Phase I: Semi-Automated Sports Video Search

SBIR 第一阶段：半自动体育视频搜索

• 批准号: 0810428
• 负责人: Michael Fleischman
• 金额: --
• 依托单位: Bluefin Lab, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0810428&HistoricalAwards=false
• 关键词: SBIR; Phase; Semi; Automated; Sports

This Small Business Innovation Research Phase I project will develop new technology that will enable precise search of sports videos. Users will be able to search for specific players, teams, and plays from large archives of recorded video sports broadcasts. The proposed research will build on early results of a sports video search engine developed by the team at MIT. The approach combines semantic information mined from speech transcriptions with visual information extracted using video analysis algorithms. The proposed research will extend the existing software algorithms that have been developed for baseball video to other professional and college sports. Additional software tools will be developed to increase the accuracy of the search system, and new user interfaces based on natural language processing algorithms will be designed to enable simplified user access to video. The anticipated result of this research is a method for accurate video search and indexing that enables queries by natural language and requires significantly less human labor to initially tag video than existing techniques. The broader impact of this research comes from the commercialization of this technology as a service layer which provides search and indexing solutions to multiple market segments that together represent a multibillion dollar industry in the United States. The research meets the needs of at least three market segments: (1) Sports professionals, who will gain powerful video access tools enabling better player evaluation, recruiting, coaching, and game analysis; (2) Sports news providers, who will be able to link news stories to related video clips thereby adding value to their media offerings; (3) Sports fans, who will be able to search and browse sports video archives with ease, providing new opportunities for advertising. Initial market research suggests that the access enabled by this technology would have broad impact on how sports video is used. Furthermore, the approach may later be extended to apply beyond sports to other video domains.

这个小型企业创新研究第一阶段项目将开发新技术，使体育视频的精确搜索成为可能。用户将能够搜索特定的球员，球队，并发挥从大型档案记录的视频体育广播。这项拟议中的研究将建立在麻省理工学院团队开发的体育视频搜索引擎的早期成果之上。该方法将从语音翻译中挖掘的语义信息与使用视频分析算法提取的视觉信息相结合。拟议的研究将扩展现有的软件算法，已开发的棒球视频到其他专业和大学体育。将开发更多的软件工具，以提高搜索系统的准确性，并将设计基于自然语言处理算法的新用户界面，以简化用户对视频的访问。这项研究的预期结果是一种准确的视频搜索和索引方法，可以通过自然语言进行查询，并且比现有技术需要更少的人力来初始标记视频。这项研究的更广泛的影响来自于这项技术作为服务层的商业化，它为多个细分市场提供搜索和索引解决方案，这些细分市场共同代表了美国数十亿美元的产业。这项研究至少满足了三个细分市场的需求：（1）体育专业人士，他们将获得强大的视频访问工具，从而更好地评估球员，招募，教练和比赛分析;（2）体育新闻提供商，他们将能够将新闻故事链接到相关的视频剪辑，从而为他们的媒体产品增加价值;（3）体育迷，他们将能够轻松搜索和浏览体育视频档案，为广告提供新的机会。初步的市场研究表明，这项技术实现的访问将对体育视频的使用方式产生广泛的影响。此外，该方法可以稍后扩展以应用于体育之外的其他视频域。