Physically customized DEFORMOTION models for electro-optic sensor data

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-13-M-1557
Agency Tracking Number: F12B-T06-0147
Amount: $149,166.00
Phase: Phase I
Program: STTR
Awards Year: 2013
Solicitation Year: 2012
Solicitation Topic Code: AF12-BT06
Solicitation Number: 2012.B
Small Business Information
75 Fifth Street NW, Suite 330, Atlanta, GA, -
DUNS: 078460517
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Navdeep Dahiya
 Team Leader
 (608) 373-4090
Business Contact
 Mohamed Shaib
Title: President
Phone: (404) 625-0541
Research Institution
 Georgia Institute of technology
 Anthony Yezzi
 Georgia Institute of Technolog
North Ave.
Atlanta, GA, 30332-
 (404) 894-2901
 Nonprofit college or university
ABSTRACT: In the field of computer vision, extraction of features from sensor data (EO/IR) is critical for inference tasks including target object detection, recognition, classification, segmentation and tracking. The objective of this proposal is to propose computation deformotion models that incorporate various physical properties of scene objects, particularly passenger vehicles. Layered deformotion algorithms are model-based image analysis algorithms that account for both geometric (shape and motion) as well as radiance features of scene objects. These models however, do not account for nuisance factors in radiance models, which cause mismatch between object appearance. This proposal aims to incorporate mathematical heat diffusion models for materials typically used in vehicles, in the radiance features of deformotion models. This proposal further aims to investigate other physical properties of passenger vehicles that can be incorporated into the layered deformotion models to model and mitigate the radiance model related nuisance factors, leading to more robust performance of geometric shape and appearance matching algorithms. BENEFIT: The proposed research will provide concrete mathematical models for incorporating mathematical models based on physical properties of passenger vehicles. These models will enable testing on real-world data in phase - II and eventually development of software applications useful for recognition related tasks. These applications could then be deployed for perimeter security of important buildings and installations, in Unmanned Grround and Aerial Vehicles and would be useful in both civil and defense applications.

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

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