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VAST-CQA: Video Annotation and Statistics Toolkit for Crowdsourcing Quality Assessment

Award Information
Agency: Department of Defense
Branch: National Geospatial-Intelligence Agency
Contract: HM047621C0075
Agency Tracking Number: NGA-P2-21-23
Amount: $1,000,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: NGA191-002
Solicitation Number: 19.1
Solicitation Year: 2019
Award Year: 2021
Award Start Date (Proposal Award Date): 2021-08-26
Award End Date (Contract End Date): 2023-09-06
Small Business Information
15400 Calhoun Drive Suite 190
Rockville, MD 20855-2814
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Bridget Kennedy
 (240) 599-5655
Business Contact
 Mark James
Phone: (301) 294-5221
Research Institution

The Video-National Imagery Interpretability Rating Scale (VNIIRS) is a task-based scale that reflects observable semantic content in videos. Intelligence agencies such as the NGA use VNIIRS for applications such as efficient storage and retrieval, data browsing, and testing of automated video assessment systems. Existing methods for video quality assessment rely on expert analysts to view and tag videos. Unfortunately, this approach is time-consuming, especially considering the scale of data. Crowdsourcing is attractive as an efficient approach to quickly tag large amounts of data. However, the results obtained through crowdsourcing are usually of lower quality than those obtained by expert analysts, and are sometimes noisy, missing, or incomplete as VNIIRS ratings reflect subjective assessment of semantic content. \n\n During Phase I, we have demonstrated the novel VAST-CQA annotation toolkit that allows for rapid video annotation, multi-user capabilities, smart annotation assignment, and an evaluation of an automated VNIIRS assessment system. In Phase II, we propose to extend the user interface capabilities, enhance the smart selection to expand the active learning work begun in Phase I, and further streamline the processing workflow. IAI will build and deliver the VAST-CQA software that is ready for integration at NGA by the end of Phase II.

* Information listed above is at the time of submission. *

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