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VSIIR: VNIIRS Semantics Inference for Interpretability and Rating

Award Information
Agency: Department of Defense
Branch: National Geospatial-Intelligence Agency
Contract: HM047620C0068
Agency Tracking Number: M2-0109
Amount: $1,000,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: NGA191-003
Solicitation Number: 19.1
Timeline
Solicitation Year: 2019
Award Year: 2021
Award Start Date (Proposal Award Date): 2020-11-23
Award End Date (Contract End Date): 2020-11-29
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
 Kyle Ashley
 (301) 795-2721
 kashley@i-a-i.com
Business Contact
 Mark James
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
N/A
Abstract

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 compression and data browsing. Unlike video quality metrics, VNIIRS ratings reflect subjective assessment of semantic content, which may not always be correlated with video quality metrics such as blur and noise. An automated, real-time tool that can annotate videos using its semantic content and estimate the VNIIRS rating can help analysts to analyze and search video data quickly and efficiently. \n\n The novel VSIIR framework uses state-of-the-art deep learning based techniques to estimate VNIIRS rating. The approach extracts robust temporal and semantic features from video to estimate the VNIIRS rating. The benefits of VNIIRS rating will be demonstrated using a new process framework for continuous learning and object tagging as an application.

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

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