Discovery of potent chromone-based autotaxin inhibitors inspired by cannabinoids.

Autotaxin (ATX) is an enzyme primarily known for the production of lysophosphatidic acid. Being involved in the development of major human diseases, such as cancer and neurodegenerative diseases, the enzyme has been featured in multiple studies as a pharmacological target. We previously found that the cannabinoid tetrahydrocannabinol (THC) could bind and act as an excellent inhibitor of ATX.

Fabrication of moiré on curved surfaces.

Moiré is an appealing visual effect observable when two or more repetitive patterns are superposed. Fabrication of moiré effects has already proven to be useful in a range of applications, from art to engineering. Here, we introduce a method for designing and fabricating level-line moirés on curved surfaces.

A Perception-driven Hybrid Decomposition for Multi-layer Accommodative Displays.

Multi-focal plane and multi-layered light-field displays are promising solutions for addressing all visual cues observed in the real world. Unfortunately, these devices usually require expensive optimizations to compute a suitable decomposition of the input light field or focal stack to drive individual display layers. Although these methods provide near-correct image reconstruction, a significant computational cost prevents real-time applications.

MoCap: Real-time Mobile 3D Motion Capture with a Cap-mounted Fisheye Camera.

We propose the first real-time system for the egocentric estimation of 3D human body pose in a wide range of unconstrained everyday activities. This setting has a unique set of challenges, such as mobility of the hardware setup, and robustness to long capture sessions with fast recovery from tracking failures. We tackle these challenges based on a novel lightweight setup that converts a standard baseball cap to a device for high-quality pose estimation based on a single cap-mounted fisheye camera.

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion.

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time.

Expressive Single Scattering for Light Shaft Stylization.

Light scattering in participating media is a natural phenomenon that is increasingly featured in movies and games, as it is visually pleasing and lends realism to a scene. In art, it may further be used to express a certain mood or emphasize objects. Here, artists often rely on stylization when creating scattering effects, not only because of the complexity of physically correct scattering, but also to increase expressiveness.

Multi-field Pattern Matching based on Sparse Feature Sampling.

We present an approach to pattern matching in 3D multi-field scalar data. Existing pattern matching algorithms work on single scalar or vector fields only, yet many numerical simulations output multi-field data where only a joint analysis of multiple fields describes the underlying phenomenon fully. Our method takes this into account by bundling information from multiple fields into the description of a pattern.

Fast and Memory-Efficient Topological Denoising of 2D and 3D Scalar Fields.

Data acquisition, numerical inaccuracies, and sampling often introduce noise in measurements and simulations. Removing this noise is often necessary for efficient analysis and visualization of this data, yet many denoising techniques change the minima and maxima of a scalar field. For example, the extrema can appear or disappear, spatially move, and change their value.

MovExp: A Versatile Visualization Tool for Human-Computer Interaction Studies with 3D Performance and Biomechanical Data.

In Human-Computer Interaction (HCI), experts seek to evaluate and compare the performance and ergonomics of user interfaces. Recently, a novel cost-efficient method for estimating physical ergonomics and performance has been introduced to HCI. It is based on optical motion capture and biomechanical simulation.

Property and Lighting Manipulations for Static Volume Stylization Using a Painting Metaphor.

Although volumetric phenomena are important for realistic rendering and can even be a crucial component in the image, the artistic control of the volume's appearance is challenging. Appropriate tools to edit volume properties are missing, which can make it necessary to use simulation results directly. Alternatively, high-level modifications that are rarely intuitive, e.

Real-time screen-space scattering in homogeneous environments.

The proposed screen-space algorithm approximates light scattering in homogeneous participating environments, such as water. Instead of simulating full global illumination, this method models scattering by a physically based point spread function. A discrete hierarchical convolution in a texture MIP map makes the algorithm efficient, and a custom anisotropic incremental filter prevents illumination leaking.

Markerless motion capture of multiple characters using multiview image segmentation.

Capturing the skeleton motion and detailed time-varying surface geometry of multiple, closely interacting peoples is a very challenging task, even in a multicamera setup, due to frequent occlusions and ambiguities in feature-to-person assignments. To address this task, we propose a framework that exploits multiview image segmentation. To this end, a probabilistic shape and appearance model is employed to segment the input images and to assign each pixel uniquely to one person.

Perceptually driven visibility optimization for categorical data visualization.

Visualization techniques often use color to present categorical differences to a user. When selecting a color palette, the perceptual qualities of color need careful consideration. Large coherent groups visually suppress smaller groups and are often visually dominant in images.

Precomputed Safety Shapes for Efficient and Accurate Height-Field Rendering.

Height fields have become an important element of realistic real-time image synthesis to represent surface details. In this paper, we focus on the frequent case of static height-field data, for which we can precompute acceleration structures. While many rendering algorithms exist that impose tradeoffs between speed and accuracy, we show that even accurate rendering can be combined with high performance.

Crease surfaces: from theory to extraction and application to diffusion tensor MRI.

Crease surfaces are two-dimensional manifolds along which a scalar field assumes a local maximum (ridge) or a local minimum (valley) in a constrained space. Unlike isosurfaces, they are able to capture extremal structures in the data. Creases have a long tradition in image processing and computer vision, and have recently become a popular tool for visualization.

Estimating crossing fibers: a tensor decomposition approach.

Diffusion weighted magnetic resonance imaging is a unique tool for non-invasive investigation of major nerve fiber tracts. Since the popular diffusion tensor (DT-MRI) model is limited to voxels with a single fiber direction, a number of high angular resolution techniques have been proposed to provide information about more diverse fiber distributions. Two such approaches are Q-Ball imaging and spherical deconvolution, which produce orientation distribution functions (ODFs) on the sphere.

Smoke surfaces: an interactive flow visualization technique inspired by real-world flow experiments.

Smoke rendering is a standard technique for flow visualization. Most approaches are based on a volumetric, particle based, or image based representation of the smoke. This paper introduces an alternative representation of smoke structures: as semi-transparent streak surfaces.

Visualizing transport structures of time-dependent flow fields.

This article focuses on the transport characteristics of physical properties in fluids-in particular, visualizing the finite-time transport structure of property advection. Applied to a well-chosen set of property fields, the proposed approach yields structures giving insights into the underlying flow's dynamic processes.

Reconstruction of volume data with quadratic super splines.

We propose a new approach to reconstruct nondiscrete models from gridded volume samples. As a model, we use quadratic trivariate super splines on a uniform tetrahedral partition. We discuss the smoothness and approximation properties of our model and compare to alternative piecewise polynomial constructions.

Meshless Modeling of Deformable Shapes and their Motion.

We present a new framework for interactive shape deformation modeling and key frame interpolation based on a meshless finite element formulation. Starting from a coarse nodal sampling of an object's volume, we formulate rigidity and volume preservation constraints that are enforced to yield realistic shape deformations at interactive frame rates. Additionally, by specifying key frame poses of the deforming shape and optimizing the nodal displacements while targeting smooth interpolated motion, our algorithm extends to a motion planning framework for deformable objects.

Topological visualization of brain diffusion MRI data.

Topological methods give concise and expressive visual representations of flow fields. The present work suggests a comparable method for the visualization of human brain diffusion MRI data. We explore existing techniques for the topological analysis of generic tensor fields, but find them inappropriate for diffusion MRI data.

Seeing people in different light--joint shape, motion, and reflectance capture.

By means of passive optical motion capture, real people can be authentically animated and photo-realistically textured. To import real-world characters into virtual environments, however, surface reflectance properties must also be known. We describe a video-based modeling approach that captures human shape and motion as well as reflectance characteristics from a handful of synchronized video recordings.

Multifield-graphs: an approach to visualizing correlations in multifield scalar data.

We present an approach to visualizing correlations in 3D multifield scalar data. The core of our approach is the computation of correlation fields, which are scalar fields containing the local correlations of subsets of the multiple fields. While the visualization of the correlation fields can be done using standard 3D volume visualization techniques, their huge number makes selection and handling a challenge.

Faster isosurface ray tracing using implicit KD-trees.

The visualization of high-quality isosurfaces at interactive rates is an important tool in many simulation and visualization applications. Today, isosurfaces are most often visualized by extracting a polygonal approximation that is then rendered via graphics hardware or by using a special variant of preintegrated volume rendering. However, these approaches have a number of limitations in terms of the quality of the isosurface, lack of performance for complex data sets, or supported shading models.

Topological methods for 2D time-dependent vector fields based on stream lines and path lines.

This paper describes approaches to topologically segmenting 2D time-dependent vector fields. For this class of vector fields, two important classes of lines exist: stream lines and path lines. Because of this, two segmentations are possible: either concerning the behavior of stream lines or of path lines.