This Small Business Innovation Research Phase II project will develop contextual video segmentation and automatic tagging technology and software. In long video streams that contain one or more topics, the software automatically discovers the beginnings and ends of Contextually-Coherent Video Segments in each video. Moreover, Video Semantics' technology automatically assigns textual tags to each segment such that these tags describe the topic discussed in that segment. The tags assigned make all parts of the video easily searchable. Large video producers currently depend on manually segmenting their content into small segments and assigning textual tags to these segments in order to make them searchable. A short advertisement is then inserted before each segment. This manual segmentation and tagging process represents a significant pain point for content producers because it is labor intensive and not cost effective. Meanwhile, government agencies, which continuously monitor video content depend on speech recognition to spot specified keywords. This approach inflicts two pain points: (i) analysts have to deal with large number of false detections because the context in which the keyword occurs might be irrelevant, and (ii) if the keyword occurs in an important context, analysts still need to scroll back and forth into the video to find the beginning of the relevant segment.
Video Semantics' technology and products have the potential to efficiently address significant market needs. In addition to the commercial applications, the proposed technology will enable media monitoring agencies to perform their tasks more efficiently saving valuable analyst time and resources. Moreover, because Video Semantics? technology is language-independent, media monitoring agencies will be able to monitor more content in foreign languages without the need to develop language-specific technologies. The company will employ an indirect sales strategy via partnerships with software companies that develop media monitoring solutions and metadata generation tools. The company has identified its first customer and is working with them to integrate the contextual segmentation and tagging technology with their current media monitoring solutions.
Video Semantics' SBIR Phase II project has successfully been able to develop and build algorithms and software product to extract information from online video content. The impact of the work executed in this project has made several impacts on the society as follows: Economic Impact The technology development and application has led to the formation of a technology startup business, Video Semantics. Video Semantics is located in Maryland and has been able to employ three full-time professionals, a part-time professional and a part-time college student from the University of Maryland. Video Semantics has contributed to the economic development of the local region and its technology is enabling businesses in the media broadcasting, information delivery services, education and non-profit industries to empower their businesses through the use of video content and internet technologies. Video Semantics technology is becoming a main catalyst in leveraging digital video assets available online resulting in revenue generation for advertisers, schools, video aggregators, news networks, online newspapers and many other video-based information producers; leading to improved economic strength. Education Impact Video Semantics technology allows schools, educational center and tutoring organizations to accelerate the ability to find educational content that is relevant to the interest of students. It further allows educators to empower students, improve student engagement, enhance critical thinking skills, information retention, student assessment, information retrieval, subject matter review and bookmarking. Information Delivery Impact Video producers such as news agencies, newspapers, internet information delivery power houses can now leverage more content than before, it can be shared in real-time and indexed in a meaningful objective way without subjective input from a reviewer. It supports the freedom of information, promotes awareness, contributes to knowledge sharing and allows video viewers to easily identify content that is relevant and of interest to their roles in the society. The video semantics technology seamlessly integrates with social networks and allows internet search engines to provide more contextual and relevant content to a search query. The technology can also be used to disseminate information intelligently from public hearings, state of the union addresses, town hall meetings and other informational sessions. National Security Impact The technology developed could be used to improve national security through surveillance and monitoring of video programming and broadcasting feeds.
