You are here

Learning traffic camera locations using vehicle re-identification

Award Information
Agency: Department of Defense
Branch: National Geospatial-Intelligence Agency
Contract: HM047620C0069
Agency Tracking Number: NGA-P1-20-21
Amount: $99,519.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: NGA201-005
Solicitation Number: 20.1
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-09-30
Award End Date (Contract End Date): 2021-07-04
Small Business Information
9301 Corbin Avenue Suite 2000
Northridge, CA 91324-1111
United States
DUNS: 082191198
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Brent Woodhouse
 (818) 885-4982
Business Contact
 Greg Fetzer
Phone: (303) 651-6756
Research Institution

In its effort to provide necessary intelligence and analysis, the National Geospatial-Intelligence Agency (NGA) utilizes extensive traffic camera systems. However, the large amount of data overwhelms both analysts and existing processing methods. In order to provide a better understanding and reduce the search space for common problems such as target tracking, it is necessary to extract the camera network layout. Areté proposes the CAMEra LOcalization using Traffic (CAMELOT) solution to accomplish this by using a vehicle re-identification algorithm along with robust statistical network analysis to extract relative camera locations from traffic cameras. To do so, we will leverage Areté’s previously developed deep convolutional neural networks to create a robust solution for vehicle re-identification that considers both novel vehicle types and camera viewing geometries. The resulting vehicle re-identifications between cameras will be used to build a camera correlation matrix that defines the relative location of each camera.

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

US Flag An Official Website of the United States Government