1,765 research outputs found
Photorealistic Style Transfer with Screened Poisson Equation
Recent work has shown impressive success in transferring painterly style to
images. These approaches, however, fall short of photorealistic style transfer.
Even when both the input and reference images are photographs, the output still
exhibits distortions reminiscent of a painting. In this paper we propose an
approach that takes as input a stylized image and makes it more photorealistic.
It relies on the Screened Poisson Equation, maintaining the fidelity of the
stylized image while constraining the gradients to those of the original input
image. Our method is fast, simple, fully automatic and shows positive progress
in making a stylized image photorealistic. Our results exhibit finer details
and are less prone to artifacts than the state-of-the-art.Comment: presented in BMVC 201
Screened poisson hyperfields for shape coding
We present a novel perspective on shape characterization using the screened Poisson equation. We discuss that the effect of the screening parameter is a change of measure of the underlying metric space. Screening also indicates a conditioned random walker biased by the choice of measure. A continuum of shape fields is created by varying the screening parameter or, equivalently, the bias of the random walker. In addition to creating a regional encoding of the diffusion with a different bias, we further break down the influence of boundary interactions by considering a number of independent random walks, each emanating from a certain boundary point, whose superposition yields the screened Poisson field. Probing the screened Poisson equation from these two complementary perspectives leads to a high-dimensional hyperfield: a rich characterization of the shape that encodes global, local, interior, and boundary interactions. To extract particular shape information as needed in a compact way from the hyperfield, we apply various decompositions either to unveil parts of a shape or parts of a boundary or to create consistent mappings. The latter technique involves lower-dimensional embeddings, which we call screened Poisson encoding maps (SPEM). The expressive power of the SPEM is demonstrated via illustrative experiments as well as a quantitative shape retrieval experiment over a public benchmark database on which the SPEM method shows a high-ranking performance among the existing state-of-the-art shape retrieval methods
Covariate factor mitigation techniques for robust gait recognition
The human gait is a discriminative feature capable of recognising a person by their unique
walking manner. Currently gait recognition is based on videos captured in a controlled
environment. These videos contain challenges, termed covariate factors, which affect the
natural appearance and motion of gait, e.g. carrying a bag, clothing, shoe type and time.
However gait recognition has yet to achieve robustness to these covariate factors.
To achieve enhanced robustness capabilities, it is essential to address the existing gait
recognition limitations. Specifically, this thesis develops an understanding of how covariate
factors behave while a person is in motion and the impact covariate factors have on
the natural appearance and motion of gait. Enhanced robustness is achieved by producing
a combination of novel gait representations and novel covariate factor detection and
removal procedures.
Having addressed the limitations regarding covariate factors, this thesis achieves the goal
of robust gait recognition. Using a skeleton representation of the human figure, the Skeleton
Variance Image condenses a skeleton sequence into a single compact 2D gait representation
to express the natural gait motion. In addition, a covariate factor detection
and removal module is used to maximise the mitigation of covariate factor effects. By
establishing the average pixel distribution within training (covariate factor free) representations,
a comparison against test (covariate factor) representations achieves effective
covariate factor detection. The corresponding difference can effectively remove covariate
factors which occur at the boundary of, and hidden within, the human figure.The Engineering and Physical Sciences Research Council (EPSRC
Coulomb screening in mesoscopic noise: a kinetic approach
Coulomb screening, together with degeneracy, is characteristic of the
metallic electron gas. While there is little trace of its effects in transport
and noise in the bulk, at mesoscopic scales the electronic fluctuations start
to show appreciable Coulomb correlations. Within a strictly standard Boltzmann
and Fermi-liquid framework, we analyze these phenomena and their relation to
the mesoscopic fluctuation-dissipation theorem, which we prove. We identify two
distinct screening mechanisms for mesoscopic fluctuations. One is the
self-consistent response of the contact potential in a non-uniform system. The
other couples to scattering, and is an exclusively non-equilibrium process.
Contact-potential effects renormalize all thermal fluctuations, at all scales.
Collisional effects are relatively short-ranged and modify non-equilibrium
noise. We discuss ways to detect these differences experimentally.Comment: Source: REVTEX. 16 pp.; 7 Postscript figs. Accepted for publication
in J. Phys.: Cond. Ma
Optimal Navigation Functions for Nonlinear Stochastic Systems
This paper presents a new methodology to craft navigation functions for
nonlinear systems with stochastic uncertainty. The method relies on the
transformation of the Hamilton-Jacobi-Bellman (HJB) equation into a linear
partial differential equation. This approach allows for optimality criteria to
be incorporated into the navigation function, and generalizes several existing
results in navigation functions. It is shown that the HJB and that existing
navigation functions in the literature sit on ends of a spectrum of
optimization problems, upon which tradeoffs may be made in problem complexity.
In particular, it is shown that under certain criteria the optimal navigation
function is related to Laplace's equation, previously used in the literature,
through an exponential transform. Further, analytical solutions to the HJB are
available in simplified domains, yielding guidance towards optimality for
approximation schemes. Examples are used to illustrate the role that noise, and
optimality can potentially play in navigation system design.Comment: Accepted to IROS 2014. 8 Page
A particle method for the homogeneous Landau equation
We propose a novel deterministic particle method to numerically approximate
the Landau equation for plasmas. Based on a new variational formulation in
terms of gradient flows of the Landau equation, we regularize the collision
operator to make sense of the particle solutions. These particle solutions
solve a large coupled ODE system that retains all the important properties of
the Landau operator, namely the conservation of mass, momentum and energy, and
the decay of entropy. We illustrate our new method by showing its performance
in several test cases including the physically relevant case of the Coulomb
interaction. The comparison to the exact solution and the spectral method is
strikingly good maintaining 2nd order accuracy. Moreover, an efficient
implementation of the method via the treecode is explored. This gives a proof
of concept for the practical use of our method when coupled with the classical
PIC method for the Vlasov equation.Comment: 27 pages, 14 figures, debloated some figures, improved explanations
in sections 2, 3, and
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