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Grant: Discovery Grants Program - Individual

University of Western Ontario

$10,545.00

Recovery of 3D Information from 3D Range Data and from 2D/3D Optical Flow and 3D Scene/Range Flow

EF 2019-20

Résumé
The computation of motion via 2D/3D optical flow and 3D scene/range flow is my long term primary research interest. I have an additional primary interest in in applying these and other computational techniques to measure 3D plant growth from 3D range data in a non-invasive, non-contact manner. Over the next 5 years, my key short term primary research objectives are:***(1) To measure accurate 2D optical flow at occlusion boundaries in real image data. Currently regularization approaches produce flow that tends to ""bleed"" across occlusion edges (where the images of two differently moving objects meet). We propose to compute the flow inside of closed segmented regions to produce flow that (correctly) abruptly changes at occlusion boundaries.***(2) To measure accurate 3D scene/range flow (3D optical flow on surfaces) on stereo and range image sequences. This type of 3D optical flow measures the 3D motion of visible parts of a scene using depth maps produced from stereo images (scene flow) or directly measured using a range sensor. We hope to produce real time scene/range flow that would be useful in car driving, for example.***(3) To measure 3D quantitative plant growth from 3D range data of growing plants in a non-invasive, non-contact manner. This will allow the quantitative evaluation of a plant's growth over its life cycle. One application would be to quantify the growth rate of wild type and genetically modified plants.
Programme
Discovery Grants Program - Individual
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2017-06497
Name nom
Barron, John
Department département
Computer Science
Organization id
36
Institution établissement
University of Western Ontario
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2017
Award amount
10545
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
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
2708
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Image processing
Research subject fr
Traitement des images
Installment
inst:3 - 5
Partie
3
Nb partie
5
Application title
Recovery of 3D Information from 3D Range Data and from 2D/3D Optical Flow and 3D Scene/Range Flow
Keyword
NSERC
Application summary
The computation of motion via 2D/3D optical flow and 3D scene/range flow is my long term primary research interest. I have an additional primary interest in in applying these and other computational techniques to measure 3D plant growth from 3D range data in a non-invasive, non-contact manner. Over the next 5 years, my key short term primary research objectives are:***(1) To measure accurate 2D optical flow at occlusion boundaries in real image data. Currently regularization approaches produce flow that tends to ""bleed"" across occlusion edges (where the images of two differently moving objects meet). We propose to compute the flow inside of closed segmented regions to produce flow that (correctly) abruptly changes at occlusion boundaries.***(2) To measure accurate 3D scene/range flow (3D optical flow on surfaces) on stereo and range image sequences. This type of 3D optical flow measures the 3D motion of visible parts of a scene using depth maps produced from stereo images (scene flow) or directly measured using a range sensor. We hope to produce real time scene/range flow that would be useful in car driving, for example.***(3) To measure 3D quantitative plant growth from 3D range data of growing plants in a non-invasive, non-contact manner. This will allow the quantitative evaluation of a plant's growth over its life cycle. One application would be to quantify the growth rate of wild type and genetically modified plants.