100,974 research outputs found
Unstructured light fields
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 35-38).We present a system for interactively acquiring and rendering light fields using a hand-held commodity camera. The main challenge we address is assisting a user in achieving good coverage of the 4D domain despite the challenges of hand-held acquisition. We define coverage by bounding reprojection error between viewpoints, which accounts for all 4 dimensions of the light field. We use this criterion together with a recent Simultaneous Localization and Mapping technique to compute a coverage map on the space of viewpoints. We provide users with real-time feedback and direct them toward under-sampled parts of the light field. Our system is lightweight and has allowed us to capture hundreds of light fields. We further present a new rendering algorithm that is tailored to the unstructured yet dense data we capture. Our method can achieve piecewise-bicubic reconstruction using a triangulation of the captured viewpoints and subdivision rules applied to reconstruction weights.by Myers Abraham Davis (Abe Davis).S.M
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Opacity Light Fields: Interactive Rendering of Surface Light Fields with View-Dependent Opacity
We present new hardware-accelerated techniques for rendering surface light fields with opacity hulls that allow for interactive visualization of objects that have complex reflectance properties and elaborate geometrical details. The opacity hull is a shape enclosing the object with view-dependent opacity parameterized onto that shape. We call the combination of opacity hulls and surface light fields the opacity light field. Opacity light fields are ideally suited for rendering of the visually complex objects and scenes obtained with 3D photography. We show how to implement opacity light fields in the framework of three surface light field rendering methods: view-dependent texture mapping, unstructured lumigraph rendering, and light field mapping. The modified algorithms can be effectively supported on modern graphics hardware. Our results show that all three implementations are able to achieve interactive or real-time frame rates.Engineering and Applied Science
Inflation with a graceful exit in a random landscape
We develop a stochastic description of small-field inflationary histories
with a graceful exit in a random potential whose Hessian is a Gaussian random
matrix as a model of the unstructured part of the string landscape. The
dynamical evolution in such a random potential from a small-field inflation
region towards a viable late-time de Sitter (dS) minimum maps to the dynamics
of Dyson Brownian motion describing the relaxation of non-equilibrium
eigenvalue spectra in random matrix theory. We analytically compute the
relaxation probability in a saddle point approximation of the partition
function of the eigenvalue distribution of the Wigner ensemble describing the
mass matrices of the critical points. When applied to small-field inflation in
the landscape, this leads to an exponentially strong bias against small-field
ranges and an upper bound on the number of light fields
participating during inflation from the non-observation of negative spatial
curvature.Comment: Published versio
Learning to Synthesize a 4D RGBD Light Field from a Single Image
We present a machine learning algorithm that takes as input a 2D RGB image
and synthesizes a 4D RGBD light field (color and depth of the scene in each ray
direction). For training, we introduce the largest public light field dataset,
consisting of over 3300 plenoptic camera light fields of scenes containing
flowers and plants. Our synthesis pipeline consists of a convolutional neural
network (CNN) that estimates scene geometry, a stage that renders a Lambertian
light field using that geometry, and a second CNN that predicts occluded rays
and non-Lambertian effects. Our algorithm builds on recent view synthesis
methods, but is unique in predicting RGBD for each light field ray and
improving unsupervised single image depth estimation by enforcing consistency
of ray depths that should intersect the same scene point. Please see our
supplementary video at https://youtu.be/yLCvWoQLnmsComment: International Conference on Computer Vision (ICCV) 201
Diagnosing numerical Cherenkov instabilities in relativistic plasma simulations based on general meshes
Numerical Cherenkov radiation (NCR) or instability is a detrimental effect
frequently found in electromagnetic particle-in-cell (EM-PIC) simulations
involving relativistic plasma beams. NCR is caused by spurious coupling between
electromagnetic-field modes and multiple beam resonances. This coupling may
result from the slow down of poorly-resolved waves due to numerical (grid)
dispersion and from aliasing mechanisms. NCR has been studied in the past for
finite-difference-based EM-PIC algorithms on regular (structured) meshes with
rectangular elements. In this work, we extend the analysis of NCR to
finite-element-based EM-PIC algorithms implemented on unstructured meshes. The
influence of different mesh element shapes and mesh layouts on NCR is studied.
Analytic predictions are compared against results from finite-element-based
EM-PIC simulations of relativistic plasma beams on various mesh types.Comment: 31 pages, 20 figure
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