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Grant: Collaborative Research and Development Grants

Ryerson University

$60,000.00

Intelligent scene understanding for collaborative mobile augmented reality

EF 2018-19

Résumé
Augmented Reality (AR) is currently one of the most anticipated emerging technology, where the combination of virtual objects with the real world provide the end-user with a natural and interactive environment. AR has found its application in many fields, including digital media, entertainment, security, healthcare, etc.*Current AR technology limits the possibilities of AR through only having a rudimentary understanding of the scene surrounding a user. Partnering with AWE Company Ltd., we will develop new algorithms that will enable semantic understanding of the scene for intelligent AR, such as understanding what objects are around the user. This level of understanding will help AWE in delivering more robust AR experiences. We are especially interested in enabling collaborative AR experiences, where multiple users can enjoy and interact with the same AR experience at the same time. Specifically, we will : 1)Develop an automated method to semantically understand the user's environment. The proposed method will search the user's data (2D image and 3D point cloud) using a library of pre-trained objects, and compute locations and sizes of the identified objects. Segmenting the data and localizing detected objects will take advantage of state-of-the-art deep learning techniques to account for changes in object and environment appearance. 2. Achieve state-of-the-art in Visual-Based Localization (VBL) by using the semantic information obtained from the first contribution, and represent all the users with a common coordinate system to achieve collaborative AR. *Together, the proposed methods will result in a robust framework for creating intelligent and collaborative mobile AR applications. The proposed research will help to position Canada as a leader in multimedia technologies, while the resultant technology transfer to Canadian industry will strengthen Canada's global competitiveness and create positive impacts to Canadian economy and society.*
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
530666-2018
Name nom
Khan, Naimul
Department département
Electrical, Computer and Biomedical Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
60000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
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
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
2510
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Adaptive, learning and evolutionary systems
Research subject fr
Systèmes d'apprentissage adaptatifs et évolutifs
Partie
1
Nb partie
1
Application title
Intelligent scene understanding for collaborative mobile augmented reality
Keyword
NSERC
Application summary
Augmented Reality (AR) is currently one of the most anticipated emerging technology, where the combination of virtual objects with the real world provide the end-user with a natural and interactive environment. AR has found its application in many fields, including digital media, entertainment, security, healthcare, etc.*Current AR technology limits the possibilities of AR through only having a rudimentary understanding of the scene surrounding a user. Partnering with AWE Company Ltd., we will develop new algorithms that will enable semantic understanding of the scene for intelligent AR, such as understanding what objects are around the user. This level of understanding will help AWE in delivering more robust AR experiences. We are especially interested in enabling collaborative AR experiences, where multiple users can enjoy and interact with the same AR experience at the same time. Specifically, we will : 1)Develop an automated method to semantically understand the user's environment. The proposed method will search the user's data (2D image and 3D point cloud) using a library of pre-trained objects, and compute locations and sizes of the identified objects. Segmenting the data and localizing detected objects will take advantage of state-of-the-art deep learning techniques to account for changes in object and environment appearance. 2. Achieve state-of-the-art in Visual-Based Localization (VBL) by using the semantic information obtained from the first contribution, and represent all the users with a common coordinate system to achieve collaborative AR. *Together, the proposed methods will result in a robust framework for creating intelligent and collaborative mobile AR applications. The proposed research will help to position Canada as a leader in multimedia technologies, while the resultant technology transfer to Canadian industry will strengthen Canada's global competitiveness and create positive impacts to Canadian economy and society.*