Grant: Discovery Grants Program - Individual
University of Ontario Institute of Technology
$24,000.00
Visual Perception in Ad Hoc Networks of Smart Cameras
EF 2021-22
Résumé
I envision a future where imaging networks comprising stationary fixed cameras, hand-held camera-equipped mobile devices, and cameras mounted on autonomous platforms will collect and analyze large sums of imagery and video to support a variety of applications in areas such as infrastructure management, ecological monitoring, smart spaces for independent living, disaster readiness and response, transportation systems, personalized photo agents, etc. These networks will be an order of magnitude larger than the existing "multi-camera systems," and many scientific and technical challenges remain and much original research is needed to realize this vision. This proposal seeks funds to accelerate the development of the next generation of smart camera networks capable of unattended operation in support of urban sensing, smart environments, and scene analysis and modelling. Over the next five years, we aim to: 1) develop scientific theory for collaborative sensing in ad hoc networks of smart cameras; 2) develop theory and methods for summarizing videos captured by these networks; and 3) explore scientific and theoretical foundations for cross-view activity recognition. Work outlined in this proposal will lead to new scientific discoveries, mathematical theories, and tools for visual perception in smart camera networks. The work will also enable a myriad of smart camera networks applications. The proposal also provides exciting opportunities for unique interdisciplinary Highly Qualified Personnel (HQP) training. These HQPs will not only develop deep technical and scientific knowledge in the areas of computer vision, machine learning, camera networks, and system building, they will also learn interpersonal and oral and written communication skills. I expect that these HQPs will be in high demand in the current technology-focused job market. These HQPs will also have the opportunity to go into academia if that is where there interests lie. The outcomes of this program will directly benefit both local and international camera technology, video analytics, and digital entertainment industries, spurring economic growth. The work carried out under this proposal will adhere to the university guidelines around equity, diversity and inclusivity.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2020-05159
Name nom
Qureshi, Faisal
Department département
Science, Faculty of - Science, Faculty of
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2020
Award amount
24000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2603
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Computer vision
Research subject fr
Vision artificielle
Installment
inst:2
Partie
1
Nb partie
5
Application title
Visual Perception in Ad Hoc Networks of Smart Cameras
Keyword
NSERC
Application summary
I envision a future where imaging networks comprising stationary fixed cameras, hand-held camera-equipped mobile devices, and cameras mounted on autonomous platforms will collect and analyze large sums of imagery and video to support a variety of applications in areas such as infrastructure management, ecological monitoring, smart spaces for independent living, disaster readiness and response, transportation systems, personalized photo agents, etc. These networks will be an order of magnitude larger than the existing "multi-camera systems," and many scientific and technical challenges remain and much original research is needed to realize this vision. This proposal seeks funds to accelerate the development of the next generation of smart camera networks capable of unattended operation in support of urban sensing, smart environments, and scene analysis and modelling. Over the next five years, we aim to: 1) develop scientific theory for collaborative sensing in ad hoc networks of smart cameras; 2) develop theory and methods for summarizing videos captured by these networks; and 3) explore scientific and theoretical foundations for cross-view activity recognition. Work outlined in this proposal will lead to new scientific discoveries, mathematical theories, and tools for visual perception in smart camera networks. The work will also enable a myriad of smart camera networks applications. The proposal also provides exciting opportunities for unique interdisciplinary Highly Qualified Personnel (HQP) training. These HQPs will not only develop deep technical and scientific knowledge in the areas of computer vision, machine learning, camera networks, and system building, they will also learn interpersonal and oral and written communication skills. I expect that these HQPs will be in high demand in the current technology-focused job market. These HQPs will also have the opportunity to go into academia if that is where there interests lie. The outcomes of this program will directly benefit both local and international camera technology, video analytics, and digital entertainment industries, spurring economic growth. The work carried out under this proposal will adhere to the university guidelines around equity, diversity and inclusivity.