Grant: Alliance Grants
University of Regina
$30,000.00
AI for generating stereo disparity maps from calibrated cameras
FY 2023-24
Summary
In today's ever-evolving landscape of agriculture, precision and efficiency are the cornerstones of innovation. The goal of this collaborative partnership is to develop state-of-the-art algorithms aimed at improving the precision of agricultural tasks through camera vision technology. Specifically, our focus lies in enhancing the calculation of the disparity map via stereo imaging, a fundamental element in image-based geo-referencing for crop fields. Our pursuit of precise disparity maps holds the potential to raise to a quantum leap in the landscape of precision agriculture within Canadian industries. The benefits are multifaceted, ranging from increased crop yields and reduced waste to optimized fuel consumption and decreased CO2 emissions. This convergence of agricultural and technological advancements is part of a global race, particularly within technologically advanced nations like Canada, to design and develop new techniques for precision and efficient agriculture. These efforts play an indispensable role in maximizing the utilization of arable land and, in turn, contributing to food security on national and international scales.
Program
Alliance Grants
Recipient
Location
Saskatchewan, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
590413-2023
Name nom
Mehrandezh, Mehran M
Department département
Engineering and Applied Science, Faculty of
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2023
Award amount
30000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
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
1200
Research subject group en
Agricultural engineering
Research subject group fr
Agricultural engineering
Research subject en
Génie rural
Research subject fr
Génie rural
Application title
AI for generating stereo disparity maps from calibrated cameras
Keyword
Artificial intelligence; automated agriculture; camera projection modeling; computer vision; ego-motion analysis; image-based geo-referencing; machine learning; optimization; sensor fusion; stereo vision
Application summary
In today's ever-evolving landscape of agriculture, precision and efficiency are the cornerstones of innovation. The goal of this collaborative partnership is to develop state-of-the-art algorithms aimed at improving the precision of agricultural tasks through camera vision technology. Specifically, our focus lies in enhancing the calculation of the disparity map via stereo imaging, a fundamental element in image-based geo-referencing for crop fields. Our pursuit of precise disparity maps holds the potential to raise to a quantum leap in the landscape of precision agriculture within Canadian industries. The benefits are multifaceted, ranging from increased crop yields and reduced waste to optimized fuel consumption and decreased CO2 emissions. This convergence of agricultural and technological advancements is part of a global race, particularly within technologically advanced nations like Canada, to design and develop new techniques for precision and efficient agriculture. These efforts play an indispensable role in maximizing the utilization of arable land and, in turn, contributing to food security on national and international scales.