Abstract. This paper presents GeoS, a new algorithm for the efficient segmentation of n-dimensional image and video data. The segmentation problem is cast as approximate energy minimization in a conditional random field. A new, parallel filtering operator built upon efficient geodesic distance computation is used to propose a set of spatially smooth, contrast-sensitive segmentation hypotheses. An economical search algorithm finds the solution with minimum energy within a sensible and highly restricted subset of all possible labellings. Advantages include: i) computational efficiency with high segmentation accuracy; ii) the ability to estimate an approximation to the posterior over segmentations; iii) the ability to handle generally complex energy models. Comparison with max-flow indicates up to 60 times greater computational efficiency as well as greater memory efficiency. GeoS is validated quantitatively and qualitatively by thorough comparative experiments on existing and novel ground-truth data. Numerous results on interactive and automatic segmentation of photographs, video and volumetric medical image data are presented. 1

The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) were proposed only since the 1990s. In this work, state-of-theart sequential 2D EDT algorithms are reviewed and compared, in an effort to reach more solid conclusions regarding their differences in speed and their exactness. Six of the best algorithms were fully implemented and compared in practice.

This paper describes a method for constructing isosurface triangulations of sampled, volumetric, three-dimensional scalar fields. The resulting meshes consist of triangles that are of consistently high quality, making them well suited for accurate interpolation of scalar and vector-valued quantities, as required for numerous applications in visualization and numerical simulation. The proposed method does not rely on a local construction or adjustment of triangles as is done, for instance, in advancing wavefront or adaptive refinement methods. Instead, a system of dynamic particles optimally samples an implicit function such that the particles ’ relative positions can produce a topologically correct Delaunay triangulation. Thus, the proposed method relies on a global placement of triangle vertices. The main contributions of the paper are the integration of dynamic particles systems with surface sampling theory and PDE-based methods for controlling the local variability of particle densities, as well as detailing a practical method that accommodates Delaunay sampling requirements to generate sparse sets of points for the production of high-quality tessellations. Index Terms—Isosurface extraction, particle systems, Delaunay triangulation.

Abstract—Real-time evaluation of distributed contact forces between rigid or deformable 3D objects is a key ingredient of 6-DoF force-feedback rendering. Unfortunately, at very high temporal rates, there is often insufficient time to resolve contact between geometrically complex objects. We propose a spatially and temporally adaptive approach to approximate distributed contact forces under hard real-time constraints. Our method is CPU-based and supports contact between rigid or reduced deformable models with complex geometry. We propose a contact model that uses a point-based representation for one object and a signed-distance field for the other. This model is related to the Voxmap-PointShell (VPS) method, but gives continuous contact forces and torques, enabling stable rendering of stiff penalty-based distributed contacts. We demonstrate that stable haptic interactions can be achieved by point-sampling offset surfaces to input “polygon soup ” geometry using particle repulsion. We introduce a multiresolution nested pointshell construction that permits level-of-detail contact forces and enables graceful degradation of contact in close-proximity scenarios. Parametrically deformed distance fields are proposed for contact between reduced deformable objects. We present several examples of 6-DoF haptic rendering of geometrically complex rigid and deformable objects in distributed contact at real-time kilohertz rates.

This paper presents a new, unified technique to perform general edge-sensitive editing operations on n-dimensional images and videos efficiently. The first contribution of the paper is the introduction of a generalized geodesic distance transform (GGDT), based on soft masks. This provides a unified framework to address several, edgeaware editing operations. Diverse editing tasks such as de-noising and non-photorealistic rendering, are all dealt with fundamentally the same, fast algorithm. Second, a new, geodesic, symmetric filter (GSF) is presented which imposes contrast-sensitive spatial smoothness into segmentation and segmentation-based editing tasks (cutout, object highlightening, colorization, panorama stiching). The effect of the filter is controlled by two intuitive, geometric parameters. In contrast to existing techniques, the GSF filter is applied to real-valued pixel likelihoods (soft masks), thanks to GGDTs and it can be used for both interactive and automatic editing tasks. Complex object topologies are dealt with effortlessly. Finally, the parallelism of GGDTs enables us to exploit modern multi-core CPU architectures as well as powerful new GPUs, thus providing great flexibility of implementation and deployment. Our technique operates on both images and videos, and generalizes naturally to n-dimensional data. The proposed algorithm is validated via quantitative and qualitative comparisons with existing, state of the art approaches. Numerous results on a variety of image and video editing tasks further demonstrate the effectiveness of our method.

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Polygonal models are popular representations of 3D objects. The use of polygonal models in computational applications often requires a model to properly bound a 3D solid. That is, the polygonal model needs to be closed, manifold, and free of self-intersections. This paper surveys a sizeable literature for repairing models that do not satisfy this criteria, focusing on categorizing them by their methodology and capability. We hope to offer pointers to further readings for researchers and practitioners, and suggestions of promising directions for future research endeavors.

In this paper, we introduce the concept of isosurface similarity maps for the visualization of volume data. Isosurface similarity maps present structural information of a volume data set by depicting similarities between individual isosurfaces quantified by a robust information-theoretic measure. Unlike conventional histograms, they are not based on the frequency of isovalues and/or derivatives and therefore provide complementary information. We demonstrate that this new representation can be used to guide transfer function design and visualization parameter specification. Furthermore, we use isosurface similarity to develop an automatic parameter-free method for identifying representative isovalues. Using real-world data sets, we show that isosurface similarity maps can be a useful addition to conventional classification techniques. Categories and Subject Descriptors (according to ACM CCS): Generation—Display algorithms I.3.3 [Computer Graphics]: Picture/Image 1.

Summary. This work presents a numerical model of an idealised grain structure consisting of spheres and a method to derive the geometric characterization of the corresponding pore space. Two different starting points exist for obtaining the pore structure. Real grain structures can be obtained via computed tomography followed by image processing. Idealised grain structures, consisting of spheres, can be numerically modelled. In this paper we first concentrate on modelling, then we present a definition of pore space usable for idealised structures, but also extensible to real grain structures. Key words: pore, pore throat, modelling 1

Seismic horizons indicate change in rock properties and are central in geoscience interpretation. Traditional interpretation systems involve time consuming and repetitive manual volumetric seeding for horizon growing. We present a novel system for rapidly interpreting and visualizing seismic volumetric data. First we extract horizon surface-parts by preprocessing the seismic data. Then during interaction the user can assemble in realtime the horizon parts into horizons. Traditional interpretation systems use gradient-based illumination models in the rendering of the seismic volume and polygon rendering of horizon surfaces. We employ realtime gradientfree forward-scattering in the rendering of seismic volumes yielding results similar to high-quality global illumination. We use an implicit surface representation of horizons allowing for a seamless integration of horizon rendering and volume rendering. We present a collection of novel techniques constituting an interpretation and visualization system highly tailored to seismic data interpretation.