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Viewing sexual images is associated with reduced physiological arousal response to gambling loss.
Erotic imagery is one highly salient emotional signal that exists everywhere in daily life. The impact of sexual stimuli on human decision-making, however, has rarely been investigated. This study examines the impact of sexual stimuli on financial decision-making under risk. In each trial, either a sexual or neutral image was presented in a picture categorization task before a gambling task. Thirty-four men made gambling decisions while their physiological arousal, measured by skin conductance responses (SCRs), was recorded. Behaviorally, the proportion of gambling decisions did not differ between the sexual and neutral image trials. Physiologically, participants had smaller arousal differences, measured in micro-siemen per dollar, between losses and gains in the sexual rather than in the neutral image trials. Moreover, participants SCRs to losses relative to gains predicted the proportion of gambling decisions in the neutral image trials but not in the sexual image trials. The results were consistent with the hypothesis that the presence of emotionally salient sexual images reduces attentional and arousal-related responses to gambling losses. Our results are consistent with the theory of loss attention involving increased cognitive investment in losses compared to gains. The findings also have potential practical implications for our understanding of the specific roles of sexual images in human financial decision making in everyday life, such as gambling behaviors in the casino
Geometric Registration of High-genus Surfaces
This paper presents a method to obtain geometric registrations between
high-genus () surfaces. Surface registration between simple surfaces,
such as simply-connected open surfaces, has been well studied. However, very
few works have been carried out for the registration of high-genus surfaces.
The high-genus topology of the surface poses great challenge for surface
registration. A possible approach is to partition surfaces into
simply-connected patches and registration is done patch by patch. Consistent
cuts are required, which are usually difficult to obtain and prone to error. In
this work, we propose an effective way to obtain geometric registration between
high-genus surfaces without introducing consistent cuts. The key idea is to
conformally parameterize the surface into its universal covering space, which
is either the Euclidean plane or the hyperbolic disk embedded in
. Registration can then be done on the universal covering space
by minimizing a shape mismatching energy measuring the geometric dissimilarity
between the two surfaces. Our proposed algorithm effectively computes a smooth
registration between high-genus surfaces that matches geometric information as
much as possible. The algorithm can also be applied to find a smooth and
bijective registration minimizing any general energy functionals. Numerical
experiments on high-genus surface data show that our proposed method is
effective for registering high-genus surfaces with geometric matching. We also
applied the method to register anatomical structures for medical imaging, which
demonstrates the usefulness of the proposed algorithm
QCMC: Quasi-conformal Parameterizations for Multiply-connected domains
This paper presents a method to compute the {\it quasi-conformal
parameterization} (QCMC) for a multiply-connected 2D domain or surface. QCMC
computes a quasi-conformal map from a multiply-connected domain onto a
punctured disk associated with a given Beltrami differential. The
Beltrami differential, which measures the conformality distortion, is a
complex-valued function with supremum norm strictly less
than 1. Every Beltrami differential gives a conformal structure of . Hence,
the conformal module of , which are the radii and centers of the inner
circles, can be fully determined by , up to a M\"obius transformation. In
this paper, we propose an iterative algorithm to simultaneously search for the
conformal module and the optimal quasi-conformal parameterization. The key idea
is to minimize the Beltrami energy subject to the boundary constraints. The
optimal solution is our desired quasi-conformal parameterization onto a
punctured disk. The parameterization of the multiply-connected domain
simplifies numerical computations and has important applications in various
fields, such as in computer graphics and vision. Experiments have been carried
out on synthetic data together with real multiply-connected Riemann surfaces.
Results show that our proposed method can efficiently compute quasi-conformal
parameterizations of multiply-connected domains and outperforms other
state-of-the-art algorithms. Applications of the proposed parameterization
technique have also been explored.Comment: 26 pages, 23 figures, submitted. arXiv admin note: text overlap with
arXiv:1402.6908, arXiv:1307.2679 by other author
Fast Disk Conformal Parameterization of Simply-connected Open Surfaces
Surface parameterizations have been widely used in computer graphics and
geometry processing. In particular, as simply-connected open surfaces are
conformally equivalent to the unit disk, it is desirable to compute the disk
conformal parameterizations of the surfaces. In this paper, we propose a novel
algorithm for the conformal parameterization of a simply-connected open surface
onto the unit disk, which significantly speeds up the computation, enhances the
conformality and stability, and guarantees the bijectivity. The conformality
distortions at the inner region and on the boundary are corrected by two steps,
with the aid of an iterative scheme using quasi-conformal theories.
Experimental results demonstrate the effectiveness of our proposed method
The Theory of Computational Quasi-conformal Geometry on Point Clouds
Quasi-conformal (QC) theory is an important topic in complex analysis, which
studies geometric patterns of deformations between shapes. Recently,
computational QC geometry has been developed and has made significant
contributions to medical imaging, computer graphics and computer vision.
Existing computational QC theories and algorithms have been built on
triangulation structures. In practical situations, many 3D acquisition
techniques often produce 3D point cloud (PC) data of the object, which does not
contain connectivity information. It calls for a need to develop computational
QC theories on PCs. In this paper, we introduce the concept of computational QC
geometry on PCs. We define PC quasi-conformal (PCQC) maps and their associated
PC Beltrami coefficients (PCBCs). The PCBC is analogous to the Beltrami
differential in the continuous setting. Theoretically, we show that the PCBC
converges to its continuous counterpart as the density of the PC tends to zero.
We also theoretically and numerically validate the ability of PCBCs to measure
local geometric distortions of PC deformations. With these concepts, many
existing QC based algorithms for geometry processing and shape analysis can be
easily extended to PC data
A Conformal Approach for Surface Inpainting
We address the problem of surface inpainting, which aims to fill in holes or
missing regions on a Riemann surface based on its surface geometry. In
practical situation, surfaces obtained from range scanners often have holes
where the 3D models are incomplete. In order to analyze the 3D shapes
effectively, restoring the incomplete shape by filling in the surface holes is
necessary. In this paper, we propose a novel conformal approach to inpaint
surface holes on a Riemann surface based on its surface geometry. The basic
idea is to represent the Riemann surface using its conformal factor and mean
curvature. According to Riemann surface theory, a Riemann surface can be
uniquely determined by its conformal factor and mean curvature up to a rigid
motion. Given a Riemann surface , its mean curvature and conformal
factor can be computed easily through its conformal parameterization.
Conversely, given and , a Riemann surface can be uniquely
reconstructed by solving the Gauss-Codazzi equation on the conformal parameter
domain. Hence, the conformal factor and the mean curvature are two geometric
quantities fully describing the surface. With this - representation
of the surface, the problem of surface inpainting can be reduced to the problem
of image inpainting of and on the conformal parameter domain.
Once and are inpainted, a Riemann surface can be reconstructed
which effectively restores the 3D surface with missing holes. Since the
inpainting model is based on the geometric quantities and , the
restored surface follows the surface geometric pattern. We test the proposed
algorithm on synthetic data as well as real surface data. Experimental results
show that our proposed method is an effective surface inpainting algorithm to
fill in surface holes on an incomplete 3D models based their surface geometry.Comment: 19 pages, 12 figure
A Linear Formulation for Disk Conformal Parameterization of Simply-Connected Open Surfaces
Surface parameterization is widely used in computer graphics and geometry
processing. It simplifies challenging tasks such as surface registrations,
morphing, remeshing and texture mapping. In this paper, we present an efficient
algorithm for computing the disk conformal parameterization of simply-connected
open surfaces. A double covering technique is used to turn a simply-connected
open surface into a genus-0 closed surface, and then a fast algorithm for
parameterization of genus-0 closed surfaces can be applied. The symmetry of the
double covered surface preserves the efficiency of the computation. A planar
parameterization can then be obtained with the aid of a M\"obius transformation
and the stereographic projection. After that, a normalization step is applied
to guarantee the circular boundary. Finally, we achieve a bijective disk
conformal parameterization by a composition of quasi-conformal mappings.
Experimental results demonstrate a significant improvement in the computational
time by over 60%. At the same time, our proposed method retains comparable
accuracy, bijectivity and robustness when compared with the state-of-the-art
approaches. Applications to texture mapping are presented for illustrating the
effectiveness of our proposed algorithm
Convergence of an iterative algorithm for Teichm\"uller maps via generalized harmonic maps
Finding surface mappings with least distortion arises from many applications
in various fields. Extremal Teichm\"uller maps are surface mappings with least
conformality distortion. The existence and uniqueness of the extremal
Teichm\"uller map between Riemann surfaces of finite type are theoretically
guaranteed [1]. Recently, a simple iterative algorithm for computing the
Teichm\"uller maps between connected Riemann surfaces with given boundary
value was proposed in [11]. Numerical results was reported in the paper to show
the effectiveness of the algorithm. The method was successfully applied to
landmark-matching registration. The purpose of this paper is to prove the
iterative algorithm proposed in [11] indeed converges.Comment: 18 pages, 11 figures. arXiv admin note: text overlap with
arXiv:1005.3292 by other author
Landmark-matching Transformation with Large Deformation via n-dimensional Quasi-conformal Maps
We propose a new method to obtain landmark-matching transformations between
n-dimensional Euclidean spaces with large deformations. Given a set of feature
correspondences, our algorithm searches for an optimal folding-free mapping
that satisfies the prescribed landmark constraints. The standard conformality
distortion defined for mappings between 2-dimensional spaces is first
generalized to the -dimensional conformality distortion for a mapping
between -dimensional Euclidean spaces . We then propose a
variational model involving to tackle the landmark-matching problem in
higher dimensional spaces. The generalized conformality term enforces
the bijectivity of the optimized mapping and minimizes its local geometric
distortions even with large deformations. Another challenge is the high
computational cost of the proposed model. To tackle this, we have also proposed
a numerical method to solve the optimization problem more efficiently.
Alternating direction method with multiplier (ADMM) is applied to split the
optimization problem into two subproblems. Preconditioned conjugate gradient
method with multi-grid preconditioner is applied to solve one of the
sub-problems, while a fixed-point iteration is proposed to solve another
subproblem. Experiments have been carried out on both synthetic examples and
lung CT images to compute the diffeomorphic landmark-matching transformation
with different landmark constraints. Results show the efficacy of our proposed
model to obtain a folding-free landmark-matching transformation between
-dimensional spaces with large deformations.Comment: arXiv admin note: text overlap with arXiv:1210.8025 by other author
Image retargeting via Beltrami representation
Image retargeting aims to resize an image to one with a prescribed aspect
ratio. Simple scaling inevitably introduces unnatural geometric distortions on
the important content of the image. In this paper, we propose a simple and yet
effective method to resize an image, which preserves the geometry of the
important content, using the Beltrami representation. Our algorithm allows
users to interactively label content regions as well as line structures. Image
resizing can then be achieved by warping the image by an orientation-preserving
bijective warping map with controlled distortion. The warping map is
represented by its Beltrami representation, which captures the local geometric
distortion of the map. By carefully prescribing the values of the Beltrami
representation, images with different complexity can be effectively resized.
Our method does not require solving any optimization problems and tuning
parameters throughout the process. This results in a simple and efficient
algorithm to solve the image retargeting problem. Extensive experiments have
been carried out, which demonstrate the efficacy of our proposed method.Comment: 13pages, 13 figure
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