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Generalized Change Detection to Cue Regions of Interest

Award Information
Agency: Department of Defense
Branch: National Geospatial-Intelligence Agency
Contract: HM047619C0088
Agency Tracking Number: NGA-P2-19-11
Amount: $1,000,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: NGA181-006
Solicitation Number: 18.1
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-09-23
Award End Date (Contract End Date): 2021-09-29
Small Business Information
6800 Cortona Drive
Goleta, CA 93117
United States
DUNS: 054672662
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Matthew J Buoni
 Senior Analyst
 (805) 968-6787
 mbuoni@toyon.com
Business Contact
 SBIR Coordinator
Phone: (805) 968-6787
Email: sbir@toyon.com
Research Institution
N/A
Abstract

Toyon proposes to research and develop algorithms for generalized salient change detection, and to incorporate these algorithms into software tools implemented on the cloud. Our approach leverages the two most promising methods from Phase I, both based on supervised learning. The first method is the entropy-based feature vector and corresponding neural network, which we will apply at a coarse search (CS) resolution. We showed this approach to be successful at quantifying the scalar amount of salient change within an image, without regard to localization. The second method is an extension of semantic segmentation. We were able to show that this approach works well to classify salient-vs-non-salient change, on a pixel-by-pixel basis. We expect this approach to be effective for confirming and localizing (CL) change within a region flagged by our CS method. Training and testing this approach successfully will inevitably require labeled data, which we will create using both real images and a synthetic data generator. The result will be a cloud-based software system that flags large coarse regions of high likelihood or high amounts of change, and then proceeds to confirm and localize those changes.

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

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