79,086 research outputs found
LiveCap: Real-time Human Performance Capture from Monocular Video
We present the first real-time human performance capture approach that
reconstructs dense, space-time coherent deforming geometry of entire humans in
general everyday clothing from just a single RGB video. We propose a novel
two-stage analysis-by-synthesis optimization whose formulation and
implementation are designed for high performance. In the first stage, a skinned
template model is jointly fitted to background subtracted input video, 2D and
3D skeleton joint positions found using a deep neural network, and a set of
sparse facial landmark detections. In the second stage, dense non-rigid 3D
deformations of skin and even loose apparel are captured based on a novel
real-time capable algorithm for non-rigid tracking using dense photometric and
silhouette constraints. Our novel energy formulation leverages automatically
identified material regions on the template to model the differing non-rigid
deformation behavior of skin and apparel. The two resulting non-linear
optimization problems per-frame are solved with specially-tailored
data-parallel Gauss-Newton solvers. In order to achieve real-time performance
of over 25Hz, we design a pipelined parallel architecture using the CPU and two
commodity GPUs. Our method is the first real-time monocular approach for
full-body performance capture. Our method yields comparable accuracy with
off-line performance capture techniques, while being orders of magnitude
faster
Capturing Nucleation at 4D Atomic Resolution
Nucleation plays a critical role in many physical and biological phenomena
ranging from crystallization, melting and evaporation to the formation of
clouds and the initiation of neurodegenerative diseases. However, nucleation is
a challenging process to study in experiments especially in the early stage
when several atoms/molecules start to form a new phase from its parent phase.
Here, we advance atomic electron tomography to study early stage nucleation at
4D atomic resolution. Using FePt nanoparticles as a model system, we reveal
that early stage nuclei are irregularly shaped, each has a core of one to few
atoms with the maximum order parameter, and the order parameter gradient points
from the core to the boundary of the nucleus. We capture the structure and
dynamics of the same nuclei undergoing growth, fluctuation, dissolution,
merging and/or division, which are regulated by the order parameter
distribution and its gradient. These experimental observations differ from
classical nucleation theory (CNT) and to explain them we propose the order
parameter gradient (OPG) model. We show the OPG model generalizes CNT and
energetically favours diffuse interfaces for small nuclei and sharp interfaces
for large nuclei. We further corroborate this model using molecular dynamics
simulations of heterogeneous and homogeneous nucleation in liquid-solid phase
transitions of Pt. We anticipate that the OPG model is applicable to different
nucleation processes and our experimental method opens the door to study the
structure and dynamics of materials with 4D atomic resolution.Comment: 42 pages, 5 figures, 12 supplementary figures and one supplementary
tabl
A stable and accurate control-volume technique based on integrated radial basis function networks for fluid-flow problems
Radial basis function networks (RBFNs) have been widely used in solving partial differential equations as they
are able to provide fast convergence. Integrated RBFNs have the ability to avoid the problem of reduced convergence-rate caused by differentiation. This paper is concerned with the use of integrated RBFNs in the context of control-volume discretisations for the simulation of fluid-flow problems. Special attention is given to (i) the development of a stable high-order upwind scheme for the convection term and (ii) the development of a local high-order approximation scheme for the diffusion term. Benchmark
problems including the lid-driven triangular-cavity flow are
employed to validate the present technique. Accurate results at high values of the Reynolds number are obtained using relatively-coarse grids
Code Shrew: Software platform for teaching programming through drawings and animations
In this paper, we present Code Shrew, a new software platform accompanied by
an interactive programming course. Its aim is to teach the fundamentals of
computer programming by enabling users to create their own drawings and
animations. The programming language has a straightforward syntax based on
Python, with additions that enable easy drawing and animating using
object-oriented code. The editor reacts seamlessly and instantly, providing an
engaging and interactive environment for experimenting and testing ideas. The
programming course consists of lessons that cover essential programming
principles, as well as challenges to test users' skills as they progress
through the course. Both the lessons and challenges take advantage of the
editor's instant feedback, allowing for a focus on learning-by-doing. We
describe the software and the content, the motivation behind them, and their
connection to constructionism.Comment: 7 page
Family names as indicators of Britain’s changing regional geography
In recent years the geography of surnames has become increasingly researched in genetics, epidemiology, linguistics and geography. Surnames provide a useful data source for the analysis of population structure, migrations, genetic relationships and levels of cultural diffusion and interaction between communities. The Worldnames database (www.publicprofiler.org/worldnames) of 300 million people from 26 countries georeferenced in many cases to the equivalent of UK Postcode level provides a rich source of surname data. This work has focused on the UK component of this dataset, that is the 2001 Enhanced Electoral Role, georeferenced to Output Area level. Exploratory analysis of the distribution of surnames across the UK shows that clear regions exist, such as Cornwall, Central Wales and Scotland, in agreement with anecdotal evidence. This study is concerned with applying a wide range of methods to the UK dataset to test their sensitivity and consistency to surname regions. Methods used thus far are hierarchical and non-hierarchical clustering, barrier algorithms, such as the Monmonier Algorithm, and Multidimensional Scaling. These, to varying degrees, have highlighted the regionality of UK surnames and provide strong foundations to future work and refinement in the UK context. Establishing a firm methodology has enabled comparisons to be made with data from the Great British 1881 census, developing insights into population movements from within and outside Great Britain
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