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Grant: Department of National Defence / NSERC Research Partnership

Concordia University

$129,934.00

DEADALUS: Massive-scale urban reconstuction, classification, and rendering from remote sensor imagery

EF 2018-19

Résumé
Advances in remote sensing technologies have enabled the widespread availability of geo-imagery including satellite and oblique aerial images, and a relatively recent yet fast maturing technology called wide-area motion imagery (WAMI). Remote sensing has already been successfully employed in many applications such as intelligence, security, reconnaissance, urban planning and monitoring, etc. However, images corresponding to urban areas typically result in large volumes of data which require new computer vision and 3D graphics techniques for emerging data exploitation, including 3D reconstruction, geospatial feature classification and photorealistic rendering of the reconstructed models. Our proposed research methodology is to develop new techniques for handling big sets of large-sized images containing repetitive patterns using dense matching and deep learning for 3D reconstruction, object classification, and realistic appearance modeling. Preliminary investigations carried out by Concordia researchers have been seen by both DRDC and Presagis, a Canadian company and world leader in providing simulation, modeling, and VR software to aerospace, defense, and automotive industries, and all three partners consider it highly beneficial to persist and pursue with this research methodology. DRDC and Presagis have extensive domain knowledge, and Concordia faculty have the requisite research background and expertise. Further, Presagis has powerful software tools which will help create ground truth data needed for training deep networks, and also in validation of 3D reconstruction results. The project will facilitate training of three Doctoral and four Masters students in leading edge topics such as very large remote sensor image data processing, 3D graphics, computer vision, and deep learning, all of great interest and benefit to the Canadian scientific and industrial communities. The fundamental research and*investigations should open new ground for research in vision, graphics and airborne simulation. The results are of benefit to Canada, as it is expected that Presagis, would be able to use them to provide faster, better and globally competitive solutions to its clients worldwide.
Programme
Department of National Defence / NSERC Research Partnership
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
515566-2017
Name nom
POULLIS, CHARALAMBOS
Department département
Computer Science and Software Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2017
Award amount
129934
Program id
DNDPJ
Program name en
Department of National Defence / NSERC Research Partnership
Program name fr
Partenariat de recherche du ministère de la Défense nationale et du CRSNG
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
2603
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Computer vision
Research subject fr
Vision artificielle
Partie
1
Nb partie
1
Application title
DEADALUS: Massive-scale urban reconstuction, classification, and rendering from remote sensor imagery
Keyword
NSERC
Application summary
Advances in remote sensing technologies have enabled the widespread availability of geo-imagery including satellite and oblique aerial images, and a relatively recent yet fast maturing technology called wide-area motion imagery (WAMI). Remote sensing has already been successfully employed in many applications such as intelligence, security, reconnaissance, urban planning and monitoring, etc. However, images corresponding to urban areas typically result in large volumes of data which require new computer vision and 3D graphics techniques for emerging data exploitation, including 3D reconstruction, geospatial feature classification and photorealistic rendering of the reconstructed models. Our proposed research methodology is to develop new techniques for handling big sets of large-sized images containing repetitive patterns using dense matching and deep learning for 3D reconstruction, object classification, and realistic appearance modeling. Preliminary investigations carried out by Concordia researchers have been seen by both DRDC and Presagis, a Canadian company and world leader in providing simulation, modeling, and VR software to aerospace, defense, and automotive industries, and all three partners consider it highly beneficial to persist and pursue with this research methodology. DRDC and Presagis have extensive domain knowledge, and Concordia faculty have the requisite research background and expertise. Further, Presagis has powerful software tools which will help create ground truth data needed for training deep networks, and also in validation of 3D reconstruction results. The project will facilitate training of three Doctoral and four Masters students in leading edge topics such as very large remote sensor image data processing, 3D graphics, computer vision, and deep learning, all of great interest and benefit to the Canadian scientific and industrial communities. The fundamental research and*investigations should open new ground for research in vision, graphics and airborne simulation. The results are of benefit to Canada, as it is expected that Presagis, would be able to use them to provide faster, better and globally competitive solutions to its clients worldwide.