Generalized Image Acquisition and Analysis

From Capture to Simulation - Connecting Forward and Inverse Problems in Fluids

We explore the connection between fluid capture, simulation and proximal methods, a class of algorithms commonly used for inverse problems in image processing and computer vision. Our key finding is that the proximal operator constraining fluid velocities to be divergence-free is directly equivalent to the pressure-projection methods commonly used in incompressible flow solvers. This observation lets us treat the inverse problem of fluid tracking as a constrained flow problem all while working in an efficient, modular framework. In addition it lets us tightly couple fluid simulation into flow tracking, providing a global prior that significantly increases tracking accuracy and temporal coherence as compared to previous techniques. We demonstrate how we can use these improved results for a variety of applications, such as re-simulation, detail enhancement, and domain modification. We furthermore give an outlook of the applications beyond fluid tracking that our proximal operator framework could enable by exploring the connection of deblurring and fluid guiding.


Computational Plenoptic Imaging

Gordon Wetzstein, Ivo Ihrke, Douglas Lanman, Wolfgang Heidrich
Computer Graphics Forum 2011


The plenoptic function is a ray-based model for light that includes the color spectrum as well as spatial, temporal, and directional variation. Although digital light sensors have greatly evolved in the last years, one fundamental limitation remains: all standard CCD and CMOS sensors integrate over the dimensions of the plenoptic function as they convert photons into electrons; in the process, all visual information is irreversibly lost, except for a two-dimensional, spatially-varying subset - the common photograph. In this state of the art report, we review approaches that optically encode the dimensions of the plenpotic function transcending those captured by traditional photography and reconstruct the recorded information computationally.
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author = {Gordon Wetzstein, Ivo Ihrke, Douglas Lanman, and Wolfgang Heidrich},
title = {Computational Plenoptic Imaging},
journal = {Computer Graphics Forum},
volume = {30},
number = {8},
year = {2011},
pages = {2397--2426},
publisher = {Blackwell Publishing},
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