Reference number : GC-2017-Q1-03558, amendment number : , agreement type : G, recipient legal name : Genov, Roman (University of Toronto), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : The main objective of our research program for the next five-year term will be to design, prototype and demonstrate a new class of computational image sensor integrated circuits whose key property is that they are transport-aware. Unlike conventional image sensors, which record all incident light, transport-aware imagers can be programmed to selectively detect only some of that light, depending on the actual 3D paths it followed through a visual scene. Such an imager acquires selected components of light transport (e.g., direct-only contributions, indirect-only contributions, specular-indirect contributions, etc.) by physically blocking all &ldquo;undesirable&rdquo; light paths so they cannot contribute to the image formed on the sensor. 
 
 Transport-aware cameras promise to dominate many high-end industrial, scientific and commercial 2D and 3D imaging applications in robotics and computer vision such as: augmented and virtual reality, self-driving cars, 3D printers and scanners, video games, biomedical imaging, and materials analysis. Conventional cameras which are currently widely used for these applications have very limited programmability needed to apply transport-aware imaging techniques. Current full-functionality transport-aware cameras require a large mechanically deforming digital micromirror device (DMD) to implement programmable sensor masking, which introduces the following handicaps: (i) excessive form factor &ndash; the size of a printer &ndash; a key barrier to the largest market of portable consumer electronics; (ii) prohibitive distortion due to DMD-imposed large-lens curvature, (iii) low electro-mechanical mask update speed significantly limiting the range of applications, (iv) high power dissipation hindering mobile implementations, and (v) high cost &ndash; in the range of thousands of dollars. We will develop a new class of computational image sensors that not only eliminate DMDs and their shortfalls, but, by electronic per-pixel masking, also offer previously unattainable versatility in coded-exposure imaging. 
 
 The proposed image sensors combine spatial (intensity) and temporal (phase) exposure coding and will deliver previously unattainable performance levels to transport-aware cameras, a radically new class of cameras in their own right. Cameras based on such image sensors will offer an unrivaled view of the world around us in which refraction and scattering can be selectively attenuated or amplified and object surfaces can be reconstructed in 3D under challenging conditions well beyond of what is possible with the existing state of the art imaging technologies., program purpose french : The main objective of our research program for the next five-year term will be to design, prototype and demonstrate a new class of computational image sensor integrated circuits whose key property is that they are transport-aware. Unlike conventional image sensors, which record all incident light, transport-aware imagers can be programmed to selectively detect only some of that light, depending on the actual 3D paths it followed through a visual scene. Such an imager acquires selected components of light transport (e.g., direct-only contributions, indirect-only contributions, specular-indirect contributions, etc.) by physically blocking all &ldquo;undesirable&rdquo; light paths so they cannot contribute to the image formed on the sensor. 
 
 Transport-aware cameras promise to dominate many high-end industrial, scientific and commercial 2D and 3D imaging applications in robotics and computer vision such as: augmented and virtual reality, self-driving cars, 3D printers and scanners, video games, biomedical imaging, and materials analysis. Conventional cameras which are currently widely used for these applications have very limited programmability needed to apply transport-aware imaging techniques. Current full-functionality transport-aware cameras require a large mechanically deforming digital micromirror device (DMD) to implement programmable sensor masking, which introduces the following handicaps: (i) excessive form factor &ndash; the size of a printer &ndash; a key barrier to the largest market of portable consumer electronics; (ii) prohibitive distortion due to DMD-imposed large-lens curvature, (iii) low electro-mechanical mask update speed significantly limiting the range of applications, (iv) high power dissipation hindering mobile implementations, and (v) high cost &ndash; in the range of thousands of dollars. We will develop a new class of computational image sensors that not only eliminate DMDs and their shortfalls, but, by electronic per-pixel masking, also offer previously unattainable versatility in coded-exposure imaging. 
 
 The proposed image sensors combine spatial (intensity) and temporal (phase) exposure coding and will deliver previously unattainable performance levels to transport-aware cameras, a radically new class of cameras in their own right. Cameras based on such image sensors will offer an unrivaled view of the world around us in which refraction and scattering can be selectively attenuated or amplified and object surfaces can be reconstructed in 3D under challenging conditions well beyond of what is possible with the existing state of the art imaging technologies., agreement title english : Transport-Aware Image Sensors, agreement title french : Transport-Aware Image Sensors, agreement number : RGPIN, agreement value : 290000.0, agreement start date : 2017-05-10, 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 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), 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