SBIR Phase II: Semi-Automated Sports Video Search

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The Small Business Innovation Research (SBIR) Phase II project objective is to commercialize a novel technology for indexing video. The company's approach automatically integrates information from speech, text, and video through algorithms that generate rich semantic indexes for video. The Phase I results show that this approach can be incorporated into a system that indexes video with high accuracy and at a fraction of the cost of currently used methods. Further, during the Phase I research, the company has identified a large and growing consumer market (sports video) in which the technology can be applied. The technical objectives of the Phase II proposal focus on working with such partners to roll out initial Bluefin-powered applications, such as content-based search and video-enriched fantasy sports. Such applications are currently not feasible because of the low accuracy of automated indexing methods and the high cost of manual approaches to indexing video. Millions of hours of new video content are coming online every month, feeding an exploding demand and reshaping the nature of the Internet. Just as text-oriented search engines were necessary to empower users to find what they needed during the first phase of the text-centric Internet, a new generation of technology will be necessary to organize and effectively find content in the fast-approaching video-dominated era of the Internet. Bluefin Lab is pioneering a new approach to video organization and search by commercializing cross-modal algorithms developed in Academe. While this differentiated technology can be leveraged in several target markets, the company's initial focus is on sports media where it will power a unique experience for video search, video-enhanced fantasy sports, and other video-centric applications.