VMV14

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https://diglib.eg.org/handle/10.2312/7753

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Hierarchical Brushing of High-Dimensional Data Sets Using Quality Metrics
(The Eurographics Association, 2014) Albuquerque, Georgia; Eisemann, Martin; Löwe, Thomas; Magnor, Marcus; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
In this paper, we present an interactive exploration framework that puts the human-in-the-loop with the application of quality metrics and brushing techniques for an efficient visual analysis of high-dimensional data sets. Our approach makes use of the human ability to distinguish interesting structures even within very cluttered projections of the data and uses quality metrics to guide the user towards such promising projections which would otherwise be difficult or time-consuming to find. Brushing the data creates new subsets that are ranked again using quality metrics and recursively analyzed by the user. This creates a human-in-the-loop approach that makes use of hierarchical brushing and quality metrics to support interactive exploratory analysis of high-dimensional data sets. We apply our approach to synthetic and real data sets, demonstrating its usefulness.
SOAR: Stochastic Optimization for Affine global point set Registration
(The Eurographics Association, 2014) Agus, Marco; Gobbetti, Enrico; Villanueva, Alberto Jaspe; Mura, Claudio; Pajarola, Renato; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
We introduce a stochastic algorithm for pairwise affine registration of partially overlapping 3D point clouds with unknown point correspondences. The algorithm recovers the globally optimal scale, rotation, and translation alignment parameters and is applicable in a variety of difficult settings, including very sparse, noisy, and outlierridden datasets that do not permit the computation of local descriptors. The technique is based on a stochastic approach for the global optimization of an alignment error function robust to noise and resistant to outliers. At each optimization step, it alternates between stochastically visiting a generalized BSP-tree representation of the current solution landscape to select a promising transformation, finding point-to-point correspondences using a GPU-accelerated technique, and incorporating new error values in the BSP tree. In contrast to previous work, instead of simply constructing the tree by guided random sampling, we exploit the problem structure through a low-cost local minimization process based on analytically solving absolute orientation problems using the current correspondences. We demonstrate the quality and performance of our method on a variety of large point sets with different scales, resolutions, and noise characteristics.
Interactive Appearance Editing in RGB-D Images
(The Eurographics Association, 2014) Bergmann, Stephan; Ritschel, Tobias; Dachsbacher, Carsten; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
The availability of increasingly powerful and affordable image and depth sensors in conjunction with the necessary processing power creates novel possibilities for more sophisticated and powerful image editing tools. Along these lines we present a method to alter the appearance of objects in RGB-D images by re-shading their surfaces with arbitrary BRDF models and subsurface scattering using the dipole diffusion approximation. To evaluate the incident light for re-shading we combine ray marching using the depth buffer as approximate geometry and environment lighting. The environment map is built from information solely contained in the RGB-D input image exploiting both the reflections on glossy surfaces as well as geometric information. Our CPU/GPU implementation provides interactive feedback to facilitate intuitive editing.We compare and demonstrate our method with rendered images and digital photographs.
Deep Screen Space for Indirect Lighting of Volumes
(The Eurographics Association, 2014) Nalbach, Oliver; Ritschel, Tobias; Seidel, Hans-Peter; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
We present a method to render approximate indirect light transport from surfaces to volumes which is fully dynamic with respect to geometry, the medium and the main light sources, running at interactive speed. This is achieved in a three-step procedure. First, the scene is turned into a view-dependent level-of-detail surfel cloud using fast hardware tessellation. These surfels are lit and represent the senders of indirect light. Second, the current view of the volume is converted into a transmittance interval map, containing depth intervals in which the transmittance to the camera is reduced by the same fraction of the total extinction. These intervals will receive indirect illumination. Finally, surfels and intervals are linked by splatting the effect of the surfels into a hierarchical framebuffer. This linking delivers high precision between surfel-interval pairs that exchange much light and is coarser for pairs exchanging little, without constructing any explicit hierarchical data structure.
High-Speed Object Tracking Using an Asynchronous Temporal Contrast Sensor
(The Eurographics Association, 2014) Saner, Daniel; Wang, Oliver; Heinzle, Simon; Pritch, Yael; Smolic, Aljoscha; Sorkine-Hornung, Alexander; Gross, Markus; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
Purely image-based approaches to tracking objects in video sequences are more prone to failure the higher an object's speed, as it covers a greater distance over the camera's exposure time and is subject to increased motion blur. These algorithms are also susceptible to changes in the object's appearance and illumination. In this paper, we approach this problem by asynchronously recording local contrast change at high speed, using a type of visual capture device called a Dynamic Vision Sensor (DVS). We use this additional data to determine motion that takes place during the exposure of a single video frame. We present a multi-modal capture system incorporating both a DVS and a traditional video camera, a method to register the different types of sensor information, and finally apply these datasets to challenging object tracking scenarios.
Real-time Canonical-angle Views in 3D Virtual Cities
(The Eurographics Association, 2014) Kol, Timothy R.; Liao, Jingtang; Eisemann, Elmar; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
Virtual city models are useful for navigation planning or the investigation of unknown regions. However, existing rendering systems often fail to provide optimal views during the exploration, introduce occlusions, or show the buildings from the top only, which limits the amount of useful visual information accessible to the user. In consequence, users are forced to interact more extensively with the application to avoid these shortcomings. This process can be quite time-consuming. In this paper, we propose a new technique based on canonical views to address these problems. We compute every building's canonical view and, dynamically, transform it correspondingly, so that it is easy to identify under all camera angles. A user study was conducted to assess how this technique compares to a regular view; our method improves the recognizability of the buildings and helps the users explore the virtual city more efficiently. The results indicate that using canonical views is beneficial for efficient navigation in virtual cities.
Online Adaptive PCA for Inverse Kinematics Hand Tracking
(The Eurographics Association, 2014) Schröder, Matthias; Botsch, Mario; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
Recent approaches to real-time bare hand tracking estimate the hand's pose and posture by fitting a virtual hand model to RGBD sensor data using inverse kinematics. It has been shown that exploiting natural hand synergies can improve the efficiency and quality of the tracking, by performing the optimization in a reduced parameter space consisting of realistic hand postures [SMRB14]. The downside, however, is that only postures within this subspace can be tracked reliably, thereby trading off flexibility and accuracy for performance and robustness. In this paper we extend the previous method by introducing an adaptive synergistic model that is automatically adjusted to observed hand articulations that are not covered by the initial subspace. Our adaptive model combines the robustness of tracking in a reduced parameter space with the flexibility of optimizing for the full articulation of the hand, which we demonstrate in several synthetic and real-world experiments.
Curvature-Based Crease Surfaces for Wave Visualization
(The Eurographics Association, 2014) Aldrich, Garrett; Gimenez, Alfredo; Oskin, Michael; Strelitz, Richard; Woodring, Jonathan; Kellogg, Louise H.; Hamann, Bernd; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
The visualization and analysis of complex fields often requires identifying and extracting domain specific features. Through a collaboration with geophysicists we extend previous work on crease surfaces with a new and complimentary definition: extremas in principal surface curvature rather than scalar value. Using this definition, we visualize the resulting surfaces which correspond to individual wave fronts. As these wave fronts propagate through a control structure (medium), they undergo changes in intensity, shape and topology due to reflection, refraction and interference. We demonstrate our ability to effectively visualize these phenomena in complex data sets including a large-scale simulation of a hypothetical earthquake along the San Andreas fault in Southern California.
Towards Efficient Online Compression of Incrementally Acquired Point Clouds
(The Eurographics Association, 2014) Golla, Tim; Schwartz, Christopher; Klein, Reinhard; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
We present a framework for the online compression of incrementally acquired point cloud data. For this, we extend an existing vector quantization-based offline point cloud compression algorithm to handle the challenges that arise from the envisioned online scenario. In particular, we learn a codebook in advance from training data and replace a computationally demanding part of the algorithm with a faster alternative. We show that the compression ratios and reconstruction quality are comparable to the offline version while the speed is sufficiently improved. Furthermore, we investigate how well codebooks that are generated from different amounts of training data generalize to larger sets of point cloud data.
Exploring Simulation in Sensor Network Models
(The Eurographics Association, 2014) Steiger, Martin; Hutter, Marco; Schader, Philipp; Kohlhammer, Jörn; Kuijper, Arjan; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
Simulation is an important measure to estimate different properties of a planned network such as throughput and cost. However, many parameters need to be adjusted to approximate real-world conditions properly. In this paper we present a visualization system that visually supports and guides the analysis of (physical) network simulation problems. Automatic optimizers run as a black box giving an (locally) optimal result in terms of the underlying simulation model and parameter configuration. This is often not ideal for practical usage. Our system assists the user in the process of comparing different simulations to quickly achieve the optimal configuration in terms of user preference. It highlights differences between simulation runs and indicates which parameter modification leads to the best improvement. We expect that this results in large time savings for the domain expert while configuring the simulation system.
Automated Detection of Anatomical Regions in Magnetic Resonance Images
(The Eurographics Association, 2014) Tóth, Márton J.; Blaskovics, Tamás; Ruskó, László; Delso, Gaspar; Csébfalvi, Balázs; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
Recognition of body parts in three-dimensional medical images is an important task in many clinical applications. It can facilitate image segmentation, registration methods and it can be the first step of an automatic image-processing workflow. In this paper, we propose an automated method to classify the axial slices of threedimensional magnetic resonance image series according to the body part they belong to. We apply the Zernike transform to obtain feature vectors representing the structural information of the axial slices. Using machine learning tools statistical correlation is found between the extracted feature vectors and the position of the slices within the human body. The initial classification is filtered by a dynamic programming based error correction method that takes the correct sequence of anatomy regions into consideration to eliminate the false recognitions. Using our approach, different body regions can be recognized at high precision rate.
On the Suitability of Connectivity-Extended Local Embedding for Drawing Multivariate Graphs
(The Eurographics Association, 2014) Fahnenschreiber, Sebastian; Laux, Melvin; Landesberger, Tatiana von; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
Multivariate networks are present in various domains such as biology, or social science. In such networks, the nodes often have several quantitative attributes, which determine similarity of nodes (e.g., person's characteristics in social networks). When interpreting these networks, often both node connectivity and node similarity need to be analyzed simultaneously. Such analysis can be supported by suitable layouts. We present and evaluate a layout for graphs with multivariate numeric attributes, which combines graph structure and node similarity. It extends local dimension reduction techniques (esp. LLE, MEU, or ISOMAP) with graph connectivity information encoded in techniques' local neighborhood function. We evaluate these extensions and available layouts using two conflicting criteria: distance preservation and graph aesthetics. Although the results vary across data sets, the new approach is able to find a balance of these criteria.
Non-local Means for Scanning Transmission Electron Microscopy Images and Poisson Noise based on Adaptive Periodic Similarity Search and Patch Regularization
(The Eurographics Association, 2014) Mevenkamp, Niklas; Yankovich, Andrew B.; Voyles, Paul M.; Berkels, Benjamin; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
High-Angle Annular Darkfield Scanning Transmission Electron Microscopy (HAADF-STEM) allows to take images at atomic scale with a contrast proportional to the atomic number. STEM acquires an image line-by-line, pixel-by-pixel leading to characteristic distortions. Furthermore, STEM images of beam sensitive materials have to be taken with short exposure times, leading to low contrast images with Poisson noise. In this paper, we propose an extension of Non-local Means (NLM) tailored to STEM images of crystalline structures. To find similar patches, we introduce an adaptive non-local search strategy that exploits the periodic structure of the crystal images. Furthermore, we extend the patch similarity measure to take into account the horizontal distortions typical for STEM images. Moreover, we discuss the Anscombe transform and the Poisson likelihood ratio to deal with Poisson noise. Finally, the resulting methods are compared to BM3D with Anscombe tranform and PURE-LET on simulated and real data.
Comparative Evaluation of Feature Line Techniques for Shape Depiction
(The Eurographics Association, 2014) Lawonn, Kai; Baer, Alexandra; Saalfeld, Patrick; Preim, Bernhard; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
This paper presents a qualitative evaluation of feature line techniques on various surfaces. We introduce the most commonly used feature lines and compare them. The techniques were analyzed with respect to the degree of realism in comparison with a shaded image with respect to the aesthetic impression they create. First, a pilot study with 20 participants was conducted to make an inquiry about their behavior and the duration. Based on the result of the pilot study, the final evaluation was carried out with 129 participants. We evaluate and interpret the trial results by using the Schulze method and give recommendations for which kind of surface, which feature line technique is most appropriate.
Supporting Urban Search & Rescue Mission Planning through Visualization-Based Analysis
(The Eurographics Association, 2014) Bock, Alexander; Kleiner, Alexander; Lundberg, Jonas; Ropinski, Timo; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
We propose a visualization system for incident commanders in urban search & rescue scenarios that supports access path planning for post-disaster structures. Utilizing point cloud data acquired from unmanned robots, we provide methods for assessment of automatically generated paths. As data uncertainty and a priori unknown information make fully automated systems impractical, we present a set of viable access paths, based on varying risk factors, in a 3D environment combined with the visual analysis tools enabling informed decisions and trade-offs. Based on these decisions, a responder is guided along the path by the incident commander, who can interactively annotate and reevaluate the acquired point cloud to react to the dynamics of the situation. We describe design considerations for our system, technical realizations, and discuss the results of an expert evaluation.
Pattern Search in Flows based on Similarity of Stream Line Segments
(The Eurographics Association, 2014) Wang, Zhongjie; Esturo, Janick Martinez; Seidel, Hans-Peter; Weinkauf, Tino; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
We propose a method that allows users to define flow features in form of patterns represented as sparse sets of stream line segments. Our approach finds ''similar'' occurrences in the same or other time steps. Related approaches define patterns using dense, local stencils or support only single segments. Our patterns are defined sparsely and can have a significant extent, i.e., they are integration-based and not local. This allows for a greater flexibility in defining features of interest. Similarity is measured using intrinsic curve properties only, which enables invariance to location, orientation, and scale. Our method starts with splitting stream lines using globally-consistent segmentation criteria. It strives to maintain the visually apparent features of the flow as a collection of stream line segments. Most importantly, it provides similar segmentations for similar flow structures. For user-defined patterns of curve segments, our algorithm finds similar ones that are invariant to similarity transformations. We showcase the utility of our method using different 2D and 3D flow fields.
Real-time Reflective and Refractive Novel-view Synthesis
(The Eurographics Association, 2014) Lochmann, Gerrit; Reinert, Bernhard; Ritschel, Tobias; Müller, Stefan; Seidel, Hans-Peter; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
We extend novel-view image synthesis from the common diffuse and opaque image formation model to the reflective and refractive case. Our approach uses a ray tree of RGBZ images, where each node contains one RGB light path which is to be warped differently depending on the depth Z and the type of path. Core of our approach are two efficient procedures for reflective and refractive warping. Different from the diffuse and opaque case, no simple direct solution exists for general geometry. Instead, a per-pixel optimization in combination with informed initial guesses warps an HD image with reflections and refractions in 18 ms on a current mobile GPU. The key application is latency avoidance in remote rendering in particular for head-mounted displays. Other applications are single-pass stereo or multi-view, motion blur and depth-of-field rendering as well as their combinations.
Efficient Self-Shadowing Using Image-Based Lighting on Glossy Surfaces
(The Eurographics Association, 2014) Knuth, Martin; Altenhofen, Christian; Kuijper, Arjan; Bender, Jan; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
In this paper we present a novel natural illumination approach for real-time rasterization-based rendering with environment map-based high dynamic range lighting. Our approach allows to use all kinds of glossiness values for surfaces, ranging continuously from completely diffuse up to mirror-like glossiness. This is achieved by combining cosine-based diffuse, glossy and mirror reflection models in one single lighting model. We approximate this model by filter functions, which are applied to the environment map. This results in a fast, image-based lookup for the different glossiness values which gives our technique the high performance that is necessary for real-time rendering. In contrast to existing real-time rasterization-based natural illumination techniques, our method has the capability of handling high gloss surfaces with directional self-occlusion. While previous works exchange the environment map by virtual point light sources in the whole lighting and shadow computation, we keep the full image information of the environment map in the lighting process and only use virtual point light sources for the shadow computation. Our technique was developed for the usage in real-time virtual prototyping systems for garments since here typically a small scene is lit by a large environment which fulfills the requirements for imagebased lighting. In this application area high performance rendering techniques for dynamic scenes are essential since a physical simulation is usually running in parallel on the same machine. However, also other applications can benefit from our approach.
Combined Three-Dimensional Visualization of Structural Connectivity and Cortex Parcellation
(The Eurographics Association, 2014) Reichenbach, Andre; Goldau, Mathias; Hlawitschka, Mario; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
The human cortex is organized in spatially distinct regions of different functional units. Cortex parcellations based on magnetic resonance imaging (MRI) of living human subjects are common practice, and recently, structural connectivity from diffusion weighted resonance imaging (dwMRI) have been successfully applied to generate such parcellations. The exploration of structural connectivity data together with cortex parcellations has proven to be challenging due to overlapping tracts and structures, limited depth perception, and the large number of tracts, which clutter the visualization. However, the involvement of structural connectivity forces such visualizations to act in anatomical space. While structural connectivity can be communicated using three-dimensional or slicebased visualizations, cortex parcellations are visualized on three-dimensional surfaces. In this work, we solve this problem by proposing an interactive illustrative 3D visualization for both structural connectivity data and cortex parcellations in anatomical space. We achieve this by providing an abstract visualization of the structural connectivity while still being able to provide the full detail on demand. Our visualization furthermore employs interactivity and illustrative depth-enhancing, which are supported by anatomical context and textual annotations and thus help the user to build a mental map of the connections in the brain. Functional and effective connectivity might benefit from such a combined visualization as they use cortex parcellations as well.
Real-time Deblocked GPU Rendering of Compressed Volumes
(The Eurographics Association, 2014) Marton, Fabio; Guitián, José A. Iglesias; Díaz, Jose; Gobbetti, Enrico; Jan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban
The wide majority of current state-of-the-art compressed GPU volume renderers are based on block-transform coding, which is susceptible to blocking artifacts, particularly at low bit-rates. In this paper we address the problem for the first time, by introducing a specialized deferred filtering architecture working on block-compressed data and including a novel deblocking algorithm. The architecture efficiently performs high quality shading of massive datasets by closely coordinating visibility- and resolution-aware adaptive data loading with GPU-accelerated per-frame data decompression, deblocking, and rendering. A thorough evaluation including quantitative and qualitative measures demonstrates the performance of our approach on large static and dynamic datasets including a massive 5124 turbulence simulation (256GB), which is aggressively compressed to less than 2 GB, so as to fully upload it on graphics board and to explore it in real-time during animation.

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