bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structure from silhouettes: a new paradigm for fast sketch‐based design of trees
Authors: Wither J. , Boudon F. , Cani M.‐P. , Godin C. 
Published: March 2009

AbstractModeling natural elements such as trees in a plausible way, while offering simple and rapid user control, is a challenge. This paper presents a method based on a new structurefrom silhouettesparadigm. We claim that sketching the silhouettes of foliage at multiple scales is quicker and more intuitive for a user than having to sketch each branch of a tree. This choice allows us to incorporate botanical knowledge, enabling us to infer branches that connect in a plausible way to their parent branch and have a correct distribution in 3D. We illustrate these ideas by presenting a seamless sketch‐based interface, used for sketching foliage silhouettes from the scale of an entire tree to the scale of a leaf. Each sketch serves for inferring both the branches at that level and construction lines to serve as support for sub‐silhouette refinement. When the user finally zooms out, the style inferred for the branching systems he has refined (in terms of branch density, angle, length distribution and shape) is duplicated to the unspecified branching systems at the same level. Meanwhile, knowledge from botany is again used for extending the branch distribution to 3D, resulting in a full, plausible 3D tree that fits the user‐sketched contours. As our results show, this system can be of interest to both experts and novice users. While experts can fully specify all parts of a tree and over‐sketch specific branches if required, any user can design a basic 3D tree in one or two minutes, as easily as sketching it with paper and pen.
Implicit Contact Handling for Deformable Objects
Authors: Otaduy Miguel A. , Tamstorf Rasmus , Steinemann Denis , Gross Markus 
Published: March 2009

AbstractWe present an algorithm for robust and efficient contact handling of deformable objects. By being aware of the internal dynamics of the colliding objects, our algorithm provides smooth rolling and sliding, stable stacking, robust impact handling, and seamless coupling of heterogeneous objects, all in a unified manner. We achieve dynamicsawareness through a constrained dynamics formulation with implicit complementarity constraints, and we present two major contributions that enable an efficient solution of the constrained dynamics problem: a time stepping algorithm that robustly ensures non‐penetration and progressively refines the formulation of constrained dynamics, and a new solver for large mixed linear complementarity problems, based on iterative constraint anticipation. We show the application of our algorithm in challenging scenarios such as multi‐layered cloth moving at high velocities, or colliding deformable solids simulated with large time steps.
Importance Sampling Spherical Harmonics
Authors: Jarosz Wojciech , Carr Nathan A. , Jensen Henrik Wann 
Published: March 2009

AbstractIn this paper we present the first practical method for importance sampling functions represented as spherical harmonics (SH). Given a spherical probability density function (PDF) represented as a vector of SH coefficients, our method warps an input point set to match the target PDF using hierarchical sample warping. Our approach is efficient and produces high quality sample distributions. As a by‐product of the sampling procedure we produce a multi‐resolution representation of the density function as either a spherical mip‐map or Haar wavelet. By exploiting this implicit conversion we can extend the method to distribute samples according to the product of an SH function with a spherical mip‐map or Haar wavelet. This generalization has immediate applicability in rendering, e.g., importance sampling the product of a BRDF and an environment map where the lighting is stored as a single high‐resolution wavelet and the BRDF is represented in spherical harmonics. Since spherical harmonics can be efficiently rotated, this product can be computed on‐the‐fly even if the BRDF is stored in local‐space. Our sampling approach generates over 6 million samples per second while significantly reducing precomputation time and storage requirements compared to previous techniques.
LazyBrush: Flexible Painting Tool for Hand‐drawn Cartoons
Authors: Sýkora Daniel , Dingliana John , Collins Steven 
Published: March 2009

AbstractIn this paper we presentLazyBrush, a novel interactive tool for painting hand‐made cartoon drawings and animations. Its key advantage is simplicity and flexibility. As opposed to previous custom tailored approaches [SBv05,QWH06]LazyBrushdoes not rely on style specific features such as homogenous regions or pattern continuity yet still offers comparable or even less manual effort for a broad class of drawing styles. In addition to this, it is not sensitive to imprecise placement of color strokes which makes painting less tedious and brings significant time savings in the context cartoon animation.LazyBrushoriginally stems from requirements analysis carried out with professional ink‐and‐paint illustrators who established a list of useful features for an ideal painting tool. We incorporate this list into an optimization framework leading to a variant of Potts energy with several interesting theoretical properties. We show how to minimize it efficiently and demonstrate its usefulness in various practical scenarios including the ink‐and‐paint production pipeline.
Compressive Dual Photography
Authors: Sen Pradeep , Darabi Soheil 
Published: March 2009

AbstractThe accurate measurement of the light transport characteristics of a complex scene is an important goal in computer graphics and has applications in relighting and dual photography. However, since the light transport data sets are typically very large, much of the previous research has focused on adaptive algorithms that capture them efficiently. In this work, we propose a novel, non‐adaptive algorithm that takes advantage of the compressibility of the light transport signal in a transform domain to capture it with less acquisitions than with standard approaches. To do this, we leverage recent work in the area of compressed sensing, where a signal is reconstructed from a few samples assuming that it is sparse in a transform domain. We demonstrate our approach by performing dual photography and relighting by using a much smaller number of acquisitions than would normally be needed. Because our algorithm is not adaptive, it is also simpler to implement than many of the current approaches.
Image Appearance Exploration by Model‐Based Navigation
Authors: Shapira L. , Shamir A. , Cohen‐Or D. 
Published: March 2009

AbstractChanging the appearance of an image can be a complex and non‐intuitive task. Many times the target image colors and look are only known vaguely and many trials are needed to reach the desired results. Moreover, the effect of a specific change on an image is difficult to envision, since one must take into account spatial image considerations along with the color constraints. Tools provided today by image processing applications can become highly technical and non‐intuitive including various gauges and knobs.In this paper we introduce a method for changing image appearance by navigation, focusing on recoloring images. The user visually navigates a high dimensional space of possible color manipulations of an image. He can either explore in it for inspiration or refine his choices by navigating into sub regions of this space to a specific goal. This navigation is enabled by modeling the chroma channels of an image's colors using a Gaussian Mixture Model (GMM). The Gaussians model both color and spatial image coordinates, and provide a high dimensional parameterization space of a rich variety of color manipulations. The user's actions are translated into transformations of the parameters of the model, which recolor the image. This approach provides both inspiration and intuitive navigation in the complex space of image color manipulations.
Spectral‐Based Group Formation Control
Authors: Takahashi Shigeo , Yoshida Kenichi , Kwon Taesoo , Lee Kang Hoon , Lee Jehee , Shin Sung Yong 
Published: March 2009

AbstractGiven a pair of keyframe formations for a group consisting of multiple individuals, we present a spectral‐based approach to smoothly transforming a source group formation into a target formation while respecting the clusters of the involved individuals. The proposed method provides an effective means for controlling the macroscopic spatiotemporal arrangement of individuals for applications such as expressive formations in mass performances and tactical formations in team sports. Our main idea is to formulate this problem as rotation interpolation of the eigenbases for the Laplacian matrices, each of which represents how the individuals are clustered in a given keyframe formation. A stream of time‐varying formations is controlled by editing the underlying adjacency relationships among individuals as well as their spatial positions at each keyframe, and interpolating the keyframe formations while producing plausible collective behaviors over a period of time. An interactive system of editing existing group behaviors in a hierarchical fashion has been implemented to provide flexible formation control of large crowds.
Animating Pictures of Fluid using Video Examples
Authors: Okabe Makoto , Anjyo Ken , Igarashi Takeo , Seidel Hans‐Peter 
Published: March 2009

AbstractWe propose a system that allows the user to design a continuous flow animation starting from a still fluid image. The basic idea is to apply the fluid motion extracted from a video example to the target image. The system first decomposes the video example into three components, an average image, a flow field and residuals. The user then specifies equivalent information over the target image. The user manually paints the rough flow field, and the system automatically refines it using the estimated gradients of the target image. The user semi‐automatically transfers the residuals onto the target image. The system then approximates the average image and synthesizes an animation on the target image by adding the transferred residuals and warping them according to the user‐specified flow field. Finally, the system adjusts the appearance of the resulting animation by applying histogram matching. We designed animations of various pictures, such as rivers, waterfalls, fires, and smoke.
Symmetry Detection Using Feature Lines
Authors: Bokeloh M. , Berner A. , Wand M. , Seidel H.‐P. , Schilling A. 
Published: March 2009

AbstractIn this paper, we describe a new algorithm for detecting structural redundancy in geometric data sets. Our algorithm computes rigid symmetries, i.e., subsets of a surface model that reoccur several times within the model differing only by translation, rotation or mirroring. Our algorithm is based on matching locally coherent constellations of feature lines on the object surfaces. In comparison to previous work, the new algorithm is able to detect a large number of symmetric parts without restrictions to regular patterns or nested hierarchies. In addition, working on relevant features only leads to a strong reduction in memory and processing costs such that very large data sets can be handled. We apply the algorithm to a number of real world 3D scanner data sets, demonstrating high recognition rates for general patterns of symmetry.
Learning good views through intelligent galleries
Authors: Vieira Thales , Bordignon Alex , Peixoto Adelailson , Tavares Geovan , Lopes Hélio , Velho Luiz , Lewiner Thomas 
Published: March 2009

AbstractThe definition of a good view of a 3D scene is highly subjective and strongly depends on both the scene content and the 3D application. Usually, camera placement is performed directly by the user, and that task may be laborious. Existing automatic virtual cameras guide the user by optimizing a single rule, e.g. maximizing the visible silhouette or the projected area. However, the use of a static pre‐defined rule may fail in respecting the user's subjective understanding of the scene. This work introduces intelligent design galleries, a learning approach for subjective problems such as the camera placement. The interaction of the user with a design gallery teaches a statistical learning machine. The trained machine can then imitate the user, either by pre‐selecting good views or by automatically placing the camera. The learning process relies on a Support Vector Machines for classifying views from a collection of descriptors, ranging from 2D image quality to 3D features visibility. Experiments of the automatic camera placement demonstrate that the proposed technique is efficient and handles scenes with occlusion and high depth complexities. This work also includes user validations of the intelligent gallery interface.
Estimating Life Expectancy in Health and Ill Health by Using a Hidden Markov Model
Authors: Van Den Hout Ardo , Jagger Carol , Matthews Fiona E. 
Published: March 2009

SummaryPopulation studies with longitudinal follow-up and mortality information can be used to estimate transitions between healthy and unhealthy states before death. When health is defined with respect to cognitive ability during old age, the trajectory of performance is either static or downwards. The paper presents a hidden Markov model to describe the underlying categorized cognitive decline, where observed improvement of cognitive ability is modelled as misclassification. Maximum likelihood is used to estimate the transition intensities between the normal cognitive state, the cognitively impaired state and death. The methodology is extended to estimate total life expectancy and life expectancy with and without cognitive impairment. The paper presents estimates from the Medical Research Council cognitive function and ageing study that began in 1991 and where individuals have had up to eight interviews over the next 10 years. It is shown that the misclassification of the states is mainly caused by not detecting an impaired state. Individuals with more years of education have lower impaired life expectancies.
Parametric Non-Mixture Cure Models for Schedule Finding of Therapeutic Agents
Authors: Liu Changying A. , Braun Thomas M. 
Published: March 2009

Summary
We propose a phase I clinical trial design that seeks to determine the cumulative safety of a series of administrations of a fixed dose of an investigational agent. In contrast with traditional phase I trials that are designed solely to find the maximum tolerated dose of the agent, our design instead identifies a maximum tolerated schedule that includes a maximum tolerated dose as well as a vector of recommended administration times. Our model is based on a non-mixture cure model that constrains the probability of dose limiting toxicity for all patients to increase monotonically with both dose and the number of administrations received. We assume a specific parametric hazard function for each administration and compute the total hazard of dose limiting toxicity for a schedule as a sum of individual administration hazards. Throughout a variety of settings motivated by an actual study in allogeneic bone marrow transplant recipients, we demonstrate that our approach has excellent operating characteristics and performs as well as the only other currently published design for schedule finding studies. We also present arguments for the preference of our non-mixture cure model over the existing model.
Seasonality with Trend and Cycle Interactions in Unobserved Components Models
Authors: Koopman Siem Jan , Lee Kai Ming 
Published: March 2009

SummaryUnobserved components time series models decompose a time series into a trend, a season, a cycle, an irregular disturbance and possibly other components. These models have been successfully applied to many economic time series. The standard assumption of a linear model, which is often appropriate after a logarithmic transformation of the data, facilitates estimation, testing, forecasting and interpretation. However, in some settings the linear–additive framework may be too restrictive. We formulate a non-linear unobserved components time series model which allows interactions between the trend–cycle component and the seasonal component. The resulting model is cast into a non-linear state space form and estimated by the extended Kalman filter, adapted for models with diffuse initial conditions. We apply our model to UK travel data and US unemployment and production series, and show that it can capture increasing seasonal variation and cycle-dependent seasonal fluctuations.
Analysis of Data from Non-Orthogonal Multistratum Designs in Industrial Experiments
Authors: Gilmour Steven G. , Goos Peter 
Published: March 2009

Summary
Split-plot and other multistratum structures are widely used in factorial and response surface experiments. Residual maximum likelihood (REML) and generalized least squares (GLS) estimation is seen as the state of the art method of data analysis for non-orthogonal designs. We analyse data from an experiment that was run to study the effects of five process factors on the drying rate for freeze-dried coffee and find that the main plot variance component is estimated to be 0. We show that this is a typical property of REML–GLS estimation in non-orthogonal split-plot designs with few main plots which is highly undesirable and can give misleading conclusions. Instead, we recommend a Bayesian analysis, using an informative prior distribution for the main plot variance component and implement this by using Markov chain Monte Carlo sampling. Paradoxically, the Bayesian analysis is less dependent on prior assumptions than the REML–GLS analysis. Bayesian analyses of the coffee freeze-drying data give more realistic conclusions than REML–GLS analysis, providing support for our recommendation.
Incidence and predictors of post‐stroke aphasia: The Arcadia Stroke Registry
Authors: Kyrozis A. , Potagas C. , Ghika A. , Tsimpouris P. K. , Virvidaki E. S. , Vemmos K. N. 
Published: March 2009

Background and purpose: Aphasia is an important post‐stroke sequela. We estimated the prevalence and main determinants of post‐stroke aphasia in the prefecture of Arcadia, Greece.Method: Prospective population‐based study of Arcadia residents diagnosed with first ever stroke. within a 2 year period. Associations of aphasia with potential predictors were analysed by logistic regression in: (i) the entire cohort and (ii) the sub‐cohort of patients who were alive 28 days post‐stroke. Multivariate regression models were adjusted for left hemispheric stroke localization and modified Rankin Scale 28 days post‐stroke (MRS‐1mo).Results: Of 555 subjects, 126 (22.7%) suffered from aphasia. When only the 405 survivors were considered, 77 (19.0%) suffered from aphasia. In adjusted multivariate models of the entire cohort, factors conferring significantly higher risk for aphasia included female gender, diabetes mellitus (borderline significance) and heart disease. In adjusted multivariate models of survivors, only diabetes was associated with significantly higher risk for aphasia.Conclusions: Female gender, diabetes and heart disease were independent prospective predictors of aphasia. The study offers a quantitative estimate of the public health problem of post‐stroke aphasia in Greece and suggests that the role of diabetes in post‐stroke aphasia may be more important than previously appreciated.
Pilot study to evaluate the efficacy and tolerability of levetiracetam (Keppra®) in treatment of patients with trigeminal neuralgia
Authors: Jorns T. P. , Johnston A. , Zakrzewska J. M. 
Published: March 2009

Background and purpose: The objective of this study was to determine whether levetiracetam (LEV) is an effective drug for treatment of trigeminal neuralgia (TN).Methods: Ten patients with TN were enrolled in a 10‐week, prospective, open‐label pilot study. The primary outcome measure was the visual analogue scale on daily pain diary and side effects. Serum levels of LEV were measured to assess correlation between drug levels and pain control.Results: There was a significant tendency towards improvement in pain severity compared with baseline in four patients with higher doses of 4 000 mg/day. The four treatment responders had less pain compared with baseline (50–90% improvement) and three subjects continued the drug after study completion. All patients rated themselves on the global evaluation scale as much improved (n = 2), minimally improved (n = 3), no change (n = 1), minimally worse (n = 2), much worse (n = 1) and very much worse (n = 1). LEV was very well tolerated and there was no difference in side effects between the low and high doses of LEV evaluations.Conclusion: Given its established safety profile, a randomized, placebo‐controlled, double‐blind trial of LEV using enhancement enrolment design is needed to confirm these open‐labelled findings using a wide variety of outcome measures.
Incidence and lifetime risk of motor neuron disease in the United Kingdom: a population‐based study
Authors: Alonso A. , Logroscino G. , Jick S. S. , Hernán M. A. 
Published: March 2009

Background and purpose: To estimate the incidence and lifetime risk of motor neuron disease (MND) in a population‐based sample in the United Kingdom.Methods: We identified new cases of MND during the period 1990–2005 in the General Practice Research Database, which includes clinical information from more than 3 million Britons enrolled with selected general practitioners. Individuals with a first medical diagnosis of MND recorded in the database were considered incident cases of the disease. The positive predictive value of the computer‐based diagnosis was estimated through review of a sample of medical records from potential MND cases.Results: In the period 1990–2005, 830 new cases of MND were identified. Age‐standardized incidence of MND was 2.6 per 100 000 persons per year in women (95% CI: 2.3, 2.8) and 3.9 in men (95% CI: 3.6, 4.3). Incidence for both sexes peaked between 75 and 79 years. The rate of MND in men was 54% higher than in women (95% CI: 33%, 77%). The lifetime risk of MND, adjusting for competing causes of death, was 1 in 472 (2.1 per 1000) in women and 1 in 350 (2.9 per 1000) in men. No increase in MND incidence over time was apparent.Conclusion: In this population‐based database, we found that MND incidence is higher in men than women, peaking in both sexes between 75 and 79 years.
The Grammar of Pneumatology in Barth and Rahner: A Reconsideration
Authors: ABLES TRAVIS 
Published: March 2009

AbstractThe trinitarian theologies of Barth and Rahner have tended to be read as failing to overcome a pneumatological deficiency that characterizes Western theology, despite the importance of their thought to proponents of the contemporary trinitarian ‘revival’. This article argues, however, that in fact their conceptualizations of the doctrine of the Trinity depend upon essential pneumatological themes: Barth's understanding of the Spirit as the subjective reality of revelation's effect, and Rahner's proposals concerning the gift of the Spirit in terms of uncreated grace and quasi‐formal causality. These insights have been largely overlooked or misconstrued, not least because both Barth and Rahner deploy their pneumatologies in the course of polemical debates with their nineteenth‐century predecessors. A fresh reading of these theologians yields a pneumatology that I characterize as a grammar of the construction of graced subjectivity.