Reference number : GC-2017-Q1-00495, amendment number : , agreement type : G, recipient legal name : Campbell, David (Simon Fraser University), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Engage Grants for Universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : The primary objective of this project is prediction of a continuous output Y from images acting as covariates X_x000D_
through a nonlinear regression function f() in the equation: Y = f(X) + residual. In order for the regression_x000D_
model to be valid all of the X covariates must have the same dimension. Unlike in most image processing_x000D_
applications images in this project are of differing sizes. In standard applications irregularly sized rectangular_x000D_
images can be transformed via compression, stretching, cropping, and padding to bring the images to a_x000D_
common size. However in our application a transformed image with a high value of Y will be equivalent to an_x000D_
un-transformed image of the same dimension with a low value of Y. In other words, the size normalizing_x000D_
transformation process induces artifacts that will destroy the regression relationship. This project expands the_x000D_
methods used for image processing to account for this type of problem. Ultimately the insights of the_x000D_
regression model will be used to predict optimal ways in which image X can be modified so as to produce an_x000D_
increased/decreased value of Y. In this project we try to predict year Y images X from an art database where_x000D_
art pieces are arbitrarily sized rectangles with any aspect ratio. Compressing an image will distort the image_x000D_
contents in ways that could be inconsistent with its time period. Cropping an image removes important_x000D_
features for prediction. Padding images with extrapolated coloured space makes the image equivalent to a_x000D_
different art piece. In such cases an early renaissance piece may become dominated by the transformation_x000D_
features making it equivalent to a recent modern art piece. The secondary goal of this work is to examine how_x000D_
to modify an art work so as to make it equivalent to an earlier or later form of that style. These methods are_x000D_
applicable to the partner company, Unbounce, in that they will assist them in advising their client customers in_x000D_
how to modify artwork optimally while maintaining it's overall style., program purpose french : The primary objective of this project is prediction of a continuous output Y from images acting as covariates X_x000D_
through a nonlinear regression function f() in the equation: Y = f(X) + residual. In order for the regression_x000D_
model to be valid all of the X covariates must have the same dimension. Unlike in most image processing_x000D_
applications images in this project are of differing sizes. In standard applications irregularly sized rectangular_x000D_
images can be transformed via compression, stretching, cropping, and padding to bring the images to a_x000D_
common size. However in our application a transformed image with a high value of Y will be equivalent to an_x000D_
un-transformed image of the same dimension with a low value of Y. In other words, the size normalizing_x000D_
transformation process induces artifacts that will destroy the regression relationship. This project expands the_x000D_
methods used for image processing to account for this type of problem. Ultimately the insights of the_x000D_
regression model will be used to predict optimal ways in which image X can be modified so as to produce an_x000D_
increased/decreased value of Y. In this project we try to predict year Y images X from an art database where_x000D_
art pieces are arbitrarily sized rectangles with any aspect ratio. Compressing an image will distort the image_x000D_
contents in ways that could be inconsistent with its time period. Cropping an image removes important_x000D_
features for prediction. Padding images with extrapolated coloured space makes the image equivalent to a_x000D_
different art piece. In such cases an early renaissance piece may become dominated by the transformation_x000D_
features making it equivalent to a recent modern art piece. The secondary goal of this work is to examine how_x000D_
to modify an art work so as to make it equivalent to an earlier or later form of that style. These methods are_x000D_
applicable to the partner company, Unbounce, in that they will assist them in advising their client customers in_x000D_
how to modify artwork optimally while maintaining it's overall style., agreement title english : Statistical models for irregularly sized objects, agreement title french : Statistical models for irregularly sized objects, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-04-25, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2018-2019), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada