642 research outputs found
3D Face Tracking and Texture Fusion in the Wild
We present a fully automatic approach to real-time 3D face reconstruction
from monocular in-the-wild videos. With the use of a cascaded-regressor based
face tracking and a 3D Morphable Face Model shape fitting, we obtain a
semi-dense 3D face shape. We further use the texture information from multiple
frames to build a holistic 3D face representation from the video frames. Our
system is able to capture facial expressions and does not require any
person-specific training. We demonstrate the robustness of our approach on the
challenging 300 Videos in the Wild (300-VW) dataset. Our real-time fitting
framework is available as an open source library at http://4dface.org
It's (Not) Your Fault! Blame and Trust Repair in Human-Agent Cooperation
Buchholz V, Kulms P, Kopp S. It's (Not) Your Fault! Blame and Trust Repair in Human-Agent Cooperation. Kognitive Systeme. 2017;2017(1).In cooperative settings the success of the team is interlinked with the performance of the individual members. Thus, the possibility to address problems and mistakes of team members needs to be given. A common means in human-human interaction is the attribution of blame. Yet, it is not clear how blame attributions affect cooperation between humans and intelligent virtual agents and the overall perception of the agent. In order to take a first step in answering these questions, a study on cooperative human-agent interaction was conducted. The study was designed to investigate the effects of two different blaming strategies used by the agent in response to an alleged goal achievement failure, that is, self-blame (agent blames itself) followed by an apology versus other-blame (agent blames the user). The results indicate that the combination of blame and trust repair enables a successful continuation of the cooperation without loss of trust and likeability
Immersed boundary parametrizations for full waveform inversion
Full Waveform Inversion (FWI) is a successful and well-established inverse
method for reconstructing material models from measured wave signals. In the
field of seismic exploration, FWI has proven particularly successful in the
reconstruction of smoothly varying material deviations. In contrast,
non-destructive testing (NDT) often requires the detection and specification of
sharp defects in a specimen. If the contrast between materials is low, FWI can
be successfully applied to these problems as well. However, so far the method
is not fully suitable to image defects such as voids, which are characterized
by a high contrast in the material parameters. In this paper, we introduce a
dimensionless scaling function to model voids in the forward and
inverse scalar wave equation problem. Depending on which material parameters
this function scales, different modeling approaches are presented,
leading to three formulations of mono-parameter FWI and one formulation of
two-parameter FWI. The resulting problems are solved by first-order
optimization, where the gradient is computed by an ajdoint state method. The
corresponding Fr\'echet kernels are derived for each approach and the
associated minimization is performed using an L-BFGS algorithm. A comparison
between the different approaches shows that scaling the density with
is most promising for parameterizing voids in the forward and inverse problem.
Finally, in order to consider arbitrary complex geometries known a priori, this
approach is combined with an immersed boundary method, the finite cell method
(FCM).Comment: 23 pages, 21 figure
Isogeometric Multi-Resolution Full Waveform Inversion based on the Finite Cell Method
Full waveform inversion (FWI) is an iterative identification process that
serves to minimize the misfit of model-based simulated and experimentally
measured wave field data, with the goal of identifying a field of parameters
for a given physical object. The inverse optimization process of FWI is based
on forward and backward solutions of the (elastic or acoustic) eave equation.
In a previous paper [1], we explored opportunities of using the finite cell
method (FCM) as the wave field solver to incorporate highly complex geometric
models. Furthermore, we demonstrated that the identification of the model's
density outperforms that of the velocity -- particularly in cases where unknown
voids characterized by homogeneous Neumann boundary conditions need to be
detected. The paper at hand extends this previous study: The isogeometric
finite cell analysis (IGA-FCM) -- a combination of isogeometric analysis (IGA)
and FCM -- is applied for the wave field solver, with the advantage that the
polynomial degree and subsequently also the sampling frequency of the wave
field can be increased quite easily. Since the inversion efficiency strongly
depends on the accuracy of the forward and backward wave field solution and of
the gradient of the functional, consistent and lumped mass matrix
discretization are compared. The resolution of the grid describing the unknown
material density is the decouple from the knot span grid. Finally, we propose
an adaptive multi-resolution algorithm that refines the material grid only
locally using an image processing-based refinement indicator. The developed
inversion framework allows fast and memory-efficient wave simulation and object
identification. While we study the general behavior of the proposed approach on
2D benchmark problems, a final 3D problem shows that it can also be used to
identify voids in geometrically complex spatial structures.Comment: 19 pages, 14 figure
Efficient multi-level hp-finite elements in arbitrary dimensions
We present an efficient algorithmic framework for constructing multi-level
hp-bases that uses a data-oriented approach that easily extends to any number
of dimensions and provides a natural framework for performance-optimized
implementations. We only operate on the bounding faces of finite elements
without considering their lower-dimensional topological features and
demonstrate the potential of the presented methods using a newly written
open-source library. First, we analyze a Fichera corner and show that the
framework does not increase runtime and memory consumption when compared
against the classical p-version of the finite element method. Then, we compute
a transient example with dynamic refinement and derefinement, where we also
obtain the expected convergence rates and excellent performance in computing
time and memory usage
A social cognition perspective on human--computer trust. The effect of perceived warmth and competence on trust in decision-making with computers
Kulms P, Kopp S. A social cognition perspective on human--computer trust. The effect of perceived warmth and competence on trust in decision-making with computers. Frontiers in Digital Humanities. Human-Media Interaction. 2018;5: 14.Trust is a crucial guide in interpersonal interactions, helping people to navigate through social decision-making problems and cooperate with others. In human–computer interaction (HCI), trustworthy computer agents foster appropriate trust by supporting a match between their perceived and actual characteristics. As computers are increasingly endowed with capabilities for cooperation and intelligent problem-solving, it is critical to ask under which conditions people discern and distinguish trustworthy from untrustworthy technology. We present an interactive cooperation game framework allowing us to capture human social attributions that indicate trust in continued and interdependent human–agent cooperation. Within this framework, we experimentally examine the impact of two key dimensions of social cognition, warmth and competence, as antecedents of behavioral trust and self-reported trustworthiness attributions of intelligent computers. Our findings suggest that, first, people infer warmth attributions from unselfish vs. selfish behavior and competence attributions from competent vs. incompetent problem-solving. Second, warmth statistically mediates the relation between unselfishness and behavioral trust as well as between unselfishness and perceived trustworthiness. We discuss the possible role of human social cognition for human–computer trust
Hand Movement Tracking Reveals Similar Processing of Anthropomorphic and Non-Anthropomorphic Cues During Attention Guiding
Kulms P, Kopp S. Hand Movement Tracking Reveals Similar Processing of Anthropomorphic and Non-Anthropomorphic Cues During Attention Guiding. Presented at the 49. Kongress der Deutschen Gesellschaft fĂĽr Psychologie, Bochum
The effect of embodiment and competence on trust and cooperation in human-agent interaction
Kulms P, Kopp S. The effect of embodiment and competence on trust and cooperation in human-agent interaction. In: Intelligent Virtual Agents. 2016: 75-84
Implicit-Explicit Time Integration for the Immersed Wave Equation
Immersed boundary methods simplify mesh generation by embedding the domain of
interest into an extended domain that is easy to mesh, introducing the
challenge of dealing with cells that intersect the domain boundary. Combined
with explicit time integration schemes, the finite cell method introduces a
lower bound for the critical time step size. Explicit transient analyses
commonly use the spectral element method due to its natural way of obtaining
diagonal mass matrices through nodal lumping. Its combination with the finite
cell method is called the spectral cell method. Unfortunately, a direct
application of nodal lumping in the spectral cell method is impossible due to
the special quadrature necessary to treat the discontinuous integrand inside
the cut cells. We analyze an implicit-explicit (IMEX) time integration method
to exploit the advantages of the nodal lumping scheme for uncut cells on one
side and the unconditional stability of implicit time integration schemes for
cut cells on the other. In this hybrid, immersed Newmark IMEX approach, we use
explicit second-order central differences to integrate the uncut degrees of
freedom that lead to a diagonal block in the mass matrix and an implicit
trapezoidal Newmark method to integrate the remaining degrees of freedom (those
supported by at least one cut cell). The immersed Newmark IMEX approach
preserves the high-order convergence rates and the geometric flexibility of the
finite cell method. We analyze a simple system of spring-coupled masses to
highlight some of the essential characteristics of Newmark IMEX time
integration. We then solve the scalar wave equation on two- and
three-dimensional examples with significant geometric complexity to show that
our approach is more efficient than state-of-the-art time integration schemes
when comparing accuracy and runtime
Acoustic Full Waveform Inversion for Ultrasonic Flaw Identification
Ultrasonic NDT is concerned with detecting flaws inside components without causing physical damage. It is possible to detect flaws using ultrasound measurements but usually no additional details about the flaw like position, dimension or orientation are available. The information about these details is hidden in the recorded experimental signals. The idea of Full Waveform Inversion is to adapt an initial simulation model of the undamaged component by minimizing the discrepancy between experimentally measured and simulated signals. Commonly, it is applied on a larger scale to infer mechanical properties of the earth in seismology [1]. We propose to use acoustic full waveform inversion for structural parameters to visualize the interior of the component. The method is adapted to US NDT by combining multiple similar experiments on the test component as the typical small amount of sensors is not sufficient for a successful imaging. It is shown that the combination of simulations and multiple experiments can be used to detect flaws and their position, dimension and orientation in emulated simulation cases
- …