3,089 research outputs found
Photorealistic ray tracing of free-space invisibility cloaks made of uniaxial dielectrics
The design rules of transformation optics generally lead to spatially
inhomogeneous and anisotropic impedance-matched magneto-dielectric material
distributions for, e.g., free-space invisibility cloaks. Recently, simplified
anisotropic non-magnetic free-space cloaks made of a locally uniaxial
dielectric material (calcite) have been realized experimentally. In a
two-dimensional setting and for in-plane polarized light propagating in this
plane, the cloaking performance can still be perfect for light rays. However,
for general views in three dimensions, various imperfections are expected. In
this paper, we study two different purely dielectric uniaxial cylindrical
free-space cloaks. For one, the optic axis is along the radial direction, for
the other one it is along the azimuthal direction. The azimuthal uniaxial cloak
has not been suggested previously to the best of our knowledge. We visualize
the cloaking performance of both by calculating photorealistic images rendered
by ray tracing. Following and complementing our previous ray-tracing work, we
use an equation of motion directly derived from Fermats principle. The rendered
images generally exhibit significant imperfections. This includes the obvious
fact that cloaking does not work at all for horizontal or for ordinary linear
polarization of light. Moreover, more subtle effects occur such as
viewing-angle-dependent aberrations. However, we still find amazingly good
cloaking performance for the purely dielectric azimuthal uniaxial cloak.Comment: 12 pages, 3 figures, journal pape
Transport-Based Neural Style Transfer for Smoke Simulations
Artistically controlling fluids has always been a challenging task.
Optimization techniques rely on approximating simulation states towards target
velocity or density field configurations, which are often handcrafted by
artists to indirectly control smoke dynamics. Patch synthesis techniques
transfer image textures or simulation features to a target flow field. However,
these are either limited to adding structural patterns or augmenting coarse
flows with turbulent structures, and hence cannot capture the full spectrum of
different styles and semantically complex structures. In this paper, we propose
the first Transport-based Neural Style Transfer (TNST) algorithm for volumetric
smoke data. Our method is able to transfer features from natural images to
smoke simulations, enabling general content-aware manipulations ranging from
simple patterns to intricate motifs. The proposed algorithm is physically
inspired, since it computes the density transport from a source input smoke to
a desired target configuration. Our transport-based approach allows direct
control over the divergence of the stylization velocity field by optimizing
incompressible and irrotational potentials that transport smoke towards
stylization. Temporal consistency is ensured by transporting and aligning
subsequent stylized velocities, and 3D reconstructions are computed by
seamlessly merging stylizations from different camera viewpoints.Comment: ACM Transaction on Graphics (SIGGRAPH ASIA 2019), additional
materials: http://www.byungsoo.me/project/neural-flow-styl
Fidelity metrics for virtual environment simulations based on spatial memory awareness states
This paper describes a methodology based on human judgments of memory awareness
states for assessing the simulation fidelity of a virtual environment (VE) in relation
to its real scene counterpart. To demonstrate the distinction between task
performance-based approaches and additional human evaluation of cognitive awareness
states, a photorealistic VE was created. Resulting scenes displayed on a headmounted
display (HMD) with or without head tracking and desktop monitor were
then compared to the real-world task situation they represented, investigating spatial
memory after exposure. Participants described how they completed their spatial
recollections by selecting one of four choices of awareness states after retrieval in
an initial test and a retention test a week after exposure to the environment. These
reflected the level of visual mental imagery involved during retrieval, the familiarity
of the recollection and also included guesses, even if informed. Experimental results
revealed variations in the distribution of participants’ awareness states across conditions
while, in certain cases, task performance failed to reveal any. Experimental
conditions that incorporated head tracking were not associated with visually induced
recollections. Generally, simulation of task performance does not necessarily
lead to simulation of the awareness states involved when completing a memory
task. The general premise of this research focuses on how tasks are achieved,
rather than only on what is achieved. The extent to which judgments of human
memory recall, memory awareness states, and presence in the physical and VE are
similar provides a fidelity metric of the simulation in question
MoSculp: Interactive Visualization of Shape and Time
We present a system that allows users to visualize complex human motion via
3D motion sculptures---a representation that conveys the 3D structure swept by
a human body as it moves through space. Given an input video, our system
computes the motion sculptures and provides a user interface for rendering it
in different styles, including the options to insert the sculpture back into
the original video, render it in a synthetic scene or physically print it.
To provide this end-to-end workflow, we introduce an algorithm that estimates
that human's 3D geometry over time from a set of 2D images and develop a
3D-aware image-based rendering approach that embeds the sculpture back into the
scene. By automating the process, our system takes motion sculpture creation
out of the realm of professional artists, and makes it applicable to a wide
range of existing video material.
By providing viewers with 3D information, motion sculptures reveal space-time
motion information that is difficult to perceive with the naked eye, and allow
viewers to interpret how different parts of the object interact over time. We
validate the effectiveness of this approach with user studies, finding that our
motion sculpture visualizations are significantly more informative about motion
than existing stroboscopic and space-time visualization methods.Comment: UIST 2018. Project page: http://mosculp.csail.mit.edu
- …