SBIR/STTR Research Award

SBIR Phase I: Multimodal Semantic Video Retrieval and Summarization

Award identifier 3b1db95d3dbf5d4d120155b97775dba6069c473b7ae153436f064ef476cbdf7eAwarding agency National Science Foundation

Award amount

$100,000

Program and phase

SBIR · Phase I

Award year

2009

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Video Semantics LLC
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
NSF 08-548
Topic code
SS

Research abstract

This Small Business Innovation Research (SBIR) Phase I project aims to develop methodology and software for highly accurate and efficient semantic video retrieval and summarization. Video Semantics will, provide personalized summaries of video content that meet users' preferences. These summaries will be based on shot granularity instead of the widely used key-frame-based summaries that are oblivious of semantics. Additionally, the proposed technology will significantly enhance online video search by enabling users to retrieve only semantically-relevant shots instead of the entire video. The key component of the software is an automated semantic video annotation system that integrates realtime video shot detection, speech recognition, natural language processing, and logic inference methods to accurately select video shots according to semantic user requests and preferences. Consumers and video content service providers will use the proposed adaptive video messaging technique to efficiently communicate queries, preferences and results using Semantic Video Summary messages (SVS). The proposed software, once commercialized, can affect a shift in the way online video content is searched and retrieved. Moreover, if successful, the software will advance the state-of-the-art of constructing video summaries, which in contrast to current technologies, accurately responds to semantic level user queries. Consequently, the software may be of interest to numerous content providers and consumers to be employed in a multitude of video applications. The software could also be integrated into the ever-popular digital video recorders to enable the owner to search large volumes of archived videos and retrieve specific ones given semantic queries, rather than the usually inaccurate file names. On the other hand, the unique summarization capabilities of the software can be used by content/service providers where personalized, semantic-based summary criteria can be predefined by the user so that the content providers, adaptively (based on network and device capabilities) stream summaries matching users' requirements to their smart phones of other mobile devices. This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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