29,965 research outputs found
Capture, Learning, and Synthesis of 3D Speaking Styles
Audio-driven 3D facial animation has been widely explored, but achieving
realistic, human-like performance is still unsolved. This is due to the lack of
available 3D datasets, models, and standard evaluation metrics. To address
this, we introduce a unique 4D face dataset with about 29 minutes of 4D scans
captured at 60 fps and synchronized audio from 12 speakers. We then train a
neural network on our dataset that factors identity from facial motion. The
learned model, VOCA (Voice Operated Character Animation) takes any speech
signal as input - even speech in languages other than English - and
realistically animates a wide range of adult faces. Conditioning on subject
labels during training allows the model to learn a variety of realistic
speaking styles. VOCA also provides animator controls to alter speaking style,
identity-dependent facial shape, and pose (i.e. head, jaw, and eyeball
rotations) during animation. To our knowledge, VOCA is the only realistic 3D
facial animation model that is readily applicable to unseen subjects without
retargeting. This makes VOCA suitable for tasks like in-game video, virtual
reality avatars, or any scenario in which the speaker, speech, or language is
not known in advance. We make the dataset and model available for research
purposes at http://voca.is.tue.mpg.de.Comment: To appear in CVPR 201
Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control
Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ânaturalâ) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control
Multi-scale statistics of turbulence motorized by active matter
A number of micro-scale biological flows are characterized by spatio-temporal
chaos. These include dense suspensions of swimming bacteria, microtubule
bundles driven by motor proteins, and dividing and migrating confluent layers
of cells. A characteristic common to all of these systems is that they are
laden with active matter, which transforms free energy in the fluid into
kinetic energy. Because of collective effects, the active matter induces
multi-scale flow motions that bear strong visual resemblance to turbulence. In
this study, multi-scale statistical tools are employed to analyze direct
numerical simulations (DNS) of periodic two- (2D) and three-dimensional (3D)
active flows and compare them to classic turbulent flows. Statistical
descriptions of the flows and their variations with activity levels are
provided in physical and spectral spaces. A scale-dependent intermittency
analysis is performed using wavelets. The results demonstrate fundamental
differences between active and high-Reynolds number turbulence; for instance,
the intermittency is smaller and less energetic in active flows, and the work
of the active stress is spectrally exerted near the integral scales and
dissipated mostly locally by viscosity, with convection playing a minor role in
momentum transport across scales.Comment: Accepted in Journal of Fluid Mechanics (2017
Low-emittance storage rings
The effects of synchrotron radiation on particle motion in storage rings are
discussed. In the absence of radiation, particle motion is symplectic, and the
beam emittances are conserved. The inclusion of radiation effects in a
classical approximation leads to emittance damping: expressions for the damping
times are derived. Then, it is shown that quantum radiation effects lead to
excitation of the beam emittances. General expressions for the equilibrium
longitudinal and horizontal (natural) emittances are derived. The impact of
lattice design on the natural emittance is discussed, with particular attention
to the special cases of FODO, achromat, and TME style lattices. Finally, the
effects of betatron coupling and vertical dispersion (generated by magnet
alignment and lattice tuning errors) on the vertical emittance are considered.Comment: Presented at the CERN Accelerator School CAS 2013: Advanced
Accelerator Physics Course, Trondheim, Norway, 18-29 August 201
Correlated continuous-time random walks: combining scale-invariance with long-range memory for spatial and temporal dynamics
Standard continuous time random walk (CTRW) models are renewal processes in
the sense that at each jump a new, independent pair of jump length and waiting
time are chosen. Globally, anomalous diffusion emerges through action of the
generalized central limit theorem leading to scale-free forms of the jump
length or waiting time distributions. Here we present a modified version of
recently proposed correlated CTRW processes, where we incorporate a power-law
correlated noise on the level of both jump length and waiting time dynamics. We
obtain a very general stochastic model, that encompasses key features of
several paradigmatic models of anomalous diffusion: discontinuous, scale-free
displacements as in Levy flights, scale-free waiting times as in subdiffusive
CTRWs, and the long-range temporal correlations of fractional Brownian motion
(FBM). We derive the exact solutions for the single-time probability density
functions and extract the scaling behaviours. Interestingly, we find that
different combinations of the model parameters lead to indistinguishable shapes
of the emerging probability density functions and identical scaling laws. Our
model will be useful to describe recent experimental single particle tracking
data, that feature a combination of CTRW and FBM properties.Comment: 25 pages, IOP style, 5 figure
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