Die »Selected Readings in Computer Graphics 2015« bestehen aus 40 ausgewählten Artikeln von insgesamt 171 wissenschaftlichen Veröffentlichungen.
Die Beiträge kommen aus dem Fraunhofer-Institut für Graphische Datenverarbeitung IGD mit Standorten in Darmstadt wie auch in Rostock, Singapur und Graz, den Partner-Instituten an den jeweiligen Universitäten, der Fachgruppe Graphisch-Interaktive Systeme der Technischen Universität Darmstadt, der Computergraphics and Communication Gruppe am Institut für Informatik der Universität Rostock, der Nanyang Technological University (NTU), Singapur, und dem Visual Computing Excellenz-Cluster der Technischen Universität Graz. Sie alle arbeiten eng in Projekten sowie Forschung und Entwicklung im Gebiet der Computer Graphik zusammen.
Alle Artikel erschienen vorher in verschiedenen wissenschaftlichen Büchern, Zeitschriften, Konferenzbänden und Workshops. Die Veröffentlichungen mussten einen gründlichen Begutachtungsprozess durch international führende Experten und etabilierte technische Vereinigungen durchlaufen. Deshalb geben die Selected Readings einen recht guten und detaillierten Überblick über die wissenschaftlichen Entwicklungen in der Computer Graphik im Jahr 2015. Sie werden von Professor Dieter W. Fellner, dem Leiter des Fraunhofer-Instituts für Graphische Datenverarbeitung IGD in Darmstadt zusammengestellt. Er ist zugleich Professor am Fachbereich Informatik der Technischen Universität Darmstadt und Professor an der Fakultät für Informatik der Technischen Universität Graz.
Die Selected Readings in Computer Graphics 2015 befassen sich mit Aspekten und Trends der Forschung und Entwicklung in Computer Graphik auf den Gebieten
- Digitale Gesellschaft
- Virtuelles Engineering
- Visuelle Entscheidungshilfe
- Visual Computing Forschung
Liste der Publikationen
Comparative Local Quality Assessment of 3D Medical Image Segmentations with Focus on Statistical Shape Model-based Algorithms
IEEE Transactions on Visualization and Computer Graphics
The quality of automatic 3D medical segmentation algorithms needs to be assessed on test datasets comprising several 3D images (i.e., instances of an organ). The experts need to compare the segmentation quality across the dataset in order to detect systematic segmentation problems. However, such comparative evaluation is not supported well by current methods. We present a novel system for assessing and comparing segmentation quality in a dataset with multiple 3D images. The data is analyzed and visualized in several views. We detect and show regions with systematic segmentation quality characteristics. For this purpose, we extended a hierarchical clustering algorithm with a connectivity criterion. We combine quality values across the dataset for determining regions with characteristic segmentation quality across instances. Using our system, the experts can also identify 3D segmentations with extraordinary quality characteristics. While we focus on algorithms based on statistical shape models, our approach can also be applied to cases, where landmark correspondences among instances can be established. We applied our approach to three real datasets: liver, cochlea and facial nerve. The segmentation experts were able to identify organ regions with systematic segmentation characteristics as well as to detect outlier instances.
Isogeometric Shell Analysis with NURBS Compatible Subdivision Surfaces
Applied Mathematics and Computation
We present a discretisation of Kirchhoff-Love thin shells based on a subdivision algorithm that generalizes NURBS to arbitrary topology. The isogeometric framework combines the advantages of both subdivision and NURBS, enabling higher degree analysis on watertight meshes of arbitrary geometry, including conic sections. Because multiple knots are supported, it is possible to benefit from symmetries in the geometry for a more efficient subdivision based analysis. The use of the new subdivision algorithm is an improvement to the flexibility of current isogeometric analysis approaches and allows new use cases.
Modeling a Virtual Robotic System for Automated 3D Digitization of Cultural Heritage Artifacts
Journal of Cultural Heritage
Complete and detailed 3D-scanning of cultural heritage artifacts is a still time-consuming process that requires skilled operators. Automating the digitization process is necessary to deal with the growing amount of artifacts available. It poses a challenging task because of the uniqueness and variety in size, shape and texture of these artifacts. Scanning devices have usually a limited focus or measurement volume and thus require precise positioning. We propose a robotic system for automated photogrammetric 3D-reconstruction. It consists of a lightweight robotic arm with a mounted camera and a turntable for the artifact. In a virtual 3D-environment, all relevant parts of the system are modeled and monitored. Here, camera views in position and orientation can be planned with respect to the depth of field of the camera, the size of the object and preferred coverage density. Given a desired view, solving inverse kinematics allows for collision-free and stable optimization of joint configurations and turntable rotation. We adopt the closed-loop inverse kinematics (CLIK) algorithm to solve the inverse kinematics on the basis of a particular definition of the orientation error. The design and parameters of the solver are described involving the option to shift the weighting between different parts of the objective function, such as precision or mechanical stability. We then use these kinematic solutions to perform the actual scanning of real objects. We conduct several tests with different kinds of objects showing reliable and sufficient results in positioning and safety. We present a visual comparison involving the real robotic system with its virtual environment demonstrating how view poses for different-sized objects are successfully planned, achieved and used for 3D-reconstruction.
Overview with Details for Exploring Geo-located Graphs on Maps
Geo-located graph drawings often suffer from map visualization problems, such as overplotting of nodes as well as edges and location of parts of the graph being outside of the screen. One cause of these problems is often an irregular distribution of nodes on the map. Zooming and panning do not solve the problems, as they either only show the overview of the whole graph or only the details of a part of the graph. We present an interactive graph drawing technique that overcomes these problems without affecting the overall geographical structure of the graph. First, we introduce a method that uses insets to visualize details of small or remote areas. Second, to prevent the subgraphs within insets from overplotting and edge crossing, we introduce a local area re-arrangement. Moreover, insets are automatically drawn/hidden and repositioned in accordance with the user's navigation. We test our technique on real-world geo-located graph data and show the effectiveness of our approach for showing overview and details at the same time. Additionally, we report on expert feedback concerning our approach.
A Cut-Cell Geometric Multigrid Poisson Solver for Fluid Simulation
Computer Graphics Forum
Annual Conference of the European Association for Computer Graphics (Eurographics) <36, 2015, Zürich, Switzerland>
We present a novel multigrid scheme based on a cut-cell formulation on regular staggered grids which generates compatible systems of linear equations on all levels of the multigrid hierarchy. This geometrically motivated formulation is derived from a finite volume approach and exhibits an improved rate of convergence compared to previous methods. Existing fluid solvers with voxelized domains can directly benefit from this approach by only modifying the representation of the non-fluid domain. The necessary building blocks are fully parallelizable and can therefore benefit from multi- and many-core architectures.
A Modular Software Architecture for Processing of Big Geospatial Data in the Cloud
Computers & Graphics
In this paper we propose a software architecture that allows for processing of large geospatial data sets in the cloud. Our system is modular and flexible and supports multiple algorithm design paradigms such as MapReduce, in-memory computing or agent-based programming. It contains a web-based user interface where domain experts (e.g. GIS analysts or urban planners) can define high-level processing workflows using a domain-specific language (DSL). The workflows are passed through a number of components including a parser, interpreter, and a service called job manager. These components use declarative and procedural knowledge encoded in rules to generate a processing chain specifying the execution of the workflows on a given cloud infrastructure according to the constraints defined by the user. The job manager evaluates this chain, spawns processing services in the cloud and monitors them. The services communicate with each other through a distributed file system that is scalable and fault-tolerant. Compared to previous work describing cloud infrastructures and architectures we focus on the processing of big heterogeneous geospatial data. In addition to that, we do not rely on only one specific programming model or a certain cloud infrastructure but support several ones. Combined with the possibility to control the processing through DSL-based workflows, this makes our architecture very flexible and configurable. We do not only see the cloud as a means to store and distribute large data sets but also as a way to harness the processing power of distributed computing environments for large-volume geospatial data sets. The proposed architecture design has been developed for the IQmulus research project funded by the European Commission. The paper concludes with the evaluation results from applying our solution to two example workflows from this project.
A Survey and Task-Based Quality Assessment of Static 2D Colormaps
Visualization and Data Analysis 2015
IS&T/SPIE Conference on Visualization and Data Analysis (VDA) <15, 2015, San Francisco, CA, USA>
Color is one of the most important visual variables since it can be combined with any other visual mapping to encode information without using additional space on the display. Encoding one or two dimensions with color is widely explored and discussed in the field. Also mapping multi-dimensional data to color is applied in a vast number of applications, either to indicate similar, or to discriminate between different elements or (multi-dimensional) structures on the screen. A variety of 2D colormaps exists in literature, covering a large variance with respect to different perceptual aspects. Many of the colormaps have a different perspective on the underlying data structure as a consequence of the various analysis tasks that exist for multivariate data. Thus, a large design space for 2D colormaps exists which makes the development and use of 2D colormaps cumbersome. According to our literature research, 2D colormaps have not been subject of in-depth quality assessment. Therefore, we present a survey of static 2D colormaps as applied for information visualization and related fields. In addition, we map seven devised quality assessment measures for 2D colormaps to seven relevant tasks for multivariate data analysis. Finally, we present the quality assessment results of the 2D colormaps with respect to the seven analysis tasks, and contribute guidelines about which colormaps to select or create for each analysis task.
A Survey of Algorithmic Shapes
In the context of computer-aided design, computer graphics and geometry processing, the idea of generative modeling is to allow the generation of highly complex objects based on a set of formal construction rules. Using these construction rules, a shape is described by a sequence of processing steps, rather than just by the result of all applied operations: shape design becomes rule design. Due to its very general nature, this approach can be applied to any domain and to any shape representation that provides a set of generating functions. The aim of this survey is to give an overview of the concepts and techniques of procedural and generative modeling, as well as their applications with a special focus on archeology and architecture.
A Visual-Interactive System for Prostate Cancer Cohort Analysis
IEEE Computer Graphics and Applications
Data-centered research is becoming increasingly important in prostate cancer research, where a long-term goal is a sound prognosis prior to surgery. The proposed visual-interactive system, developed in close collaboration with medical researchers, helps physicians efficiently and effectively visualize single and multiple patient histories at a glance.
Active Contour based Segmentation of Resected Livers in CT Images
Medical Imaging 2015: Image Processing
SPIE Medical Imaging Symposium <2015, Orlando, FL, USA>
The majority of state of the art segmentation algorithms are able to give proper results in healthy organs but not in pathological ones. However, many clinical applications require an accurate segmentation of pathological organs. The determination of the target boundaries for radiotherapy or liver volumetry calculations are examples of this. Volumetry measurements are of special interest after tumor resection for follow up of liver regrow. The segmentation of resected livers presents additional challenges that were not addressed by state of the art algorithms. This paper presents a snakes based algorithm specially developed for the segmentation of resected livers. The algorithm is enhanced with a novel dynamic smoothing technique that allows the active contour to propagate with different speeds depending on the intensities visible in its neighborhood. The algorithm is evaluated in 6 clinical CT images as well as 18 artificial datasets generated from additional clinical CT images.
Ambient Intelligence from Senior Citizens' Perspectives: Understanding Privacy Concerns, Technology Acceptance, and Expectations
European Conference on Ambient Intelligence (AmI) <12, 2015, Athens, Greece>
Especially for seniors, Ambient Intelligence can provide assistance in daily living and emergency situations, for example by automatically recognizing critical situations. The use of such systems may involve trade-offs with regard to privacy, social stigmatization, and changes of the well-known living environment. This raises the question of how older adults perceive restrictions of privacy, accept technology, and which requirements are placed on Ambient Intelligent systems. In order to better understand the related concerns and expectations, we surveyed 60 senior citizens. The results show that experience with Ambient Intelligence increases technology acceptance and reduces fears regarding privacy violations and insufficient system reliability. While participants generally tolerate a monitoring of activities in their home, including bathrooms, they do not accept commercial service providers as data recipients. A comparison between four exemplary systems shows that camera-based solutions are perceived with much greater fears than wearable emergency solutions. Burglary detection was rated as similarly important assigned as health features, whereas living comfort features were considered less useful.
An Adaptive Acceleration Structure for Screen-space Ray Tracing
Proceedings of the 7th Conference on High-Performance Graphics 2015
High-Performance Graphics (HPG) <7, 2015, Los Angeles, CA, USA>
We propose an efficient acceleration structure for real-time screenspace ray tracing. The hybrid data structure represents the scene geometry by combining a bounding volume hierarchy with local planar approximations. This enables fast empty space skipping while tracing and yields exact intersection points for the planar approximation. In combination with an occlusion-aware ray traversal our algorithm is capable to quickly trace even multiple depth layers. Compared to prior work, our technique improves the accuracy of the results, is more general, and allows for advanced image transformations, as all pixels can cast rays to arbitrary directions. We demonstrate real-time performance for several applications, including depth-of-field rendering, stereo warping, and screen-space ray traced reflections.
Animating 3D Vegetation in Real-time Using a 2D Approach
ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (i3D) <19, 2015, San Francisco, CA, USA>
In this paper, we propose a 2D approach for real-time animation of vegetation in 3D scenes, especially suitable for simulating wind effects on 3D vegetation fields with densely leaved foliage. We represent a vegetation field as view-dependent 2D billboard layers, perform a 2D harmonic motion simulation for modeling the dynamics of vegetation at the first layer (closest to the viewer), and utilize this dynamics to guide the animation of the rest of the layers while addressing the motion effects in depth and occlusion effects. As a result, our method can produce natural looking motions of vegetation swaying in wind comparable with existing commercial software, however the effort to setting up the underlying animation model and the computational cost can be significantly reduced.
Botential: Localizing On-Body Gestures by Measuring Electrical Signatures on the Human Skin
International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) <17, 2015, Copenhagen, Denmark>
We present Botential, an on-body interaction method for a wearable input device that can identify the location of onbody tapping gestures, using the entire human body as an interactive surface to expand the usually limited interaction space in the context of mobility. When the sensor is being touched, Botential identifies a body part's unique electric signature, which depends on its physiological and anatomical compositions. This input method exhibits a number of advantages over previous approaches, which include: 1) utilizing the existing signal the human body already emits, to accomplish input with various body parts, 2) the ability to also sense soft and long touches, 3) an increased sensing range that covers the whole body, and 4) the ability to detect taps and hovering through clothes.
Capacitive Proximity Sensing in Smart Environments
Journal of Ambient Intelligence and Smart Environments
To create applications for smart environments we can select from a huge variety of sensors that measure environmental parameters or detect activities of different actors within the premises. Capacitive proximity sensors use weak electric fields to recognize conductive objects, such as the human body. They can be unobtrusively applied or even provide information when hidden from view. In the past years various research groups have used this sensor category to create singular applications in this domain. On the following pages we discuss the application of capacitive proximity sensors in smart environments, establishing a classification in comparison to other sensor technologies. We give a detailed overview of the background of this sensing technology and identify specific application domains. Based on existing systems from literature and a number of prototypes we have created in the past years we can specify benefits and limitations of this technology and give a set of guidelines to researchers that are considering this technology in their smart environment applications.
CapWalk: A Capacitive Recognition of Walking-Based Activities as a Wearable Assistive Technology
Proceedings of the 8th International Conference on PErvasive Technologies Related to Assistive Environments
ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA) <8, 2015, Corfu, Greece>
In this research project, we present an alternative approach to recognize various walking-based activities based on the technology of capacitive sensing. While accelerometry-based walking detections suffer from reduced accuracy at low speeds, the technology of capacitive sensing uses physical distance parameters, which makes it invariant to the duration of step performance. Determining accurate levels of walking activity is a crucial factor for people who perform walking with tiny step lengths such as elderlies or patients with pathologic conditions. In contrast to other gait analysis solutions, CapWalk is mobile and less affected by external influences such as bad lighting conditions, while it is also invariant to external acceleration artifacts. Our approach enables a reliable recognition of very slow walking speeds, in which accelerometer-based implementations can fail or provide high deviations. In CapWalk we present three different capacitive sensing prototypes (Leg Band, Chest Band, Insole) in the setup of loading mode to demonstrate recognition of sneaking, normal walking, fast walking, jogging, and walking while carrying weight. Our designs are wearable and could easily be integrated into wearable objects, such as shoes, pants or jackets. We envision such gathered information to be used to assist certain user groups such as diabetics, whose optimal insulin dose is depending on bread units and physical activity or elderlies whose personalized dosage of medication can be better determined based on their physical activity.
Characterization of Partial Intrinsic Symmetries
Computer Vision - ECCV 2014 Workshops. Proceedings Part IV
European Conference on Computer Vision (ECCV) <13, 2014, Zurich, Switzerland>
We present a mathematical framework and algorithm for characterizing and extracting partial intrinsic symmetries of surfaces, which is a fundamental building block for many modern geometry processing algorithms. Our goal is to compute all "significant" symmetry information of the shape, which we define as r-symmetries, i.e., we report all isometric self-maps within subsets of the shape that contain at least an intrinsic circle or radius r. By specifying r, the user has direct control over the scale at which symmetry should be detected. Unlike previous techniques, we do not rely on feature points, voting or probabilistic schemes. Rather than that, we bound computational efforts by splitting our algorithm into two phases. The first detects infinitesimal r-symmetries directly using a local differential analysis, and the second performs direct matching for the remaining discrete symmetries. We show that our algorithm can successfully characterize and extract intrinsic symmetries from a number of example shapes.
CogniMeter: EEG-based Emotion, Mental Workload and Stress Visual Monitoring
2015 International Conference on Cyberworlds
International Conference on Cyberworlds (CW) <14, 2015, Visby, Sweden>
Real-time EEG (Electroencephalogram)-based user's emotion, mental workload and stress monitoring is a new direction in research and development of human-machine interfaces. It has attracted recently more attention from the research community and industry as wireless portable EEG devices became easily available on the market. EEG-based technology has been applied in anesthesiology, psychology, serious games or even in marketing. In this work, we describe available real-time algorithms of emotion recognition, mental workload, and stress recognition from EEG and propose a novel interface CogniMeter for the user's mental state visual monitoring. The system can be used in real time to assess human current emotions, levels of mental workload and stress. Currently, it is applied to monitor the user's emotional state, mental workload and stress in simulation scenarios or used as a tool to assess the subject's mental state in human factor study experiments.
Content First - A Concept for Industrial Augmented Reality Maintenance Applications using Mobile Devices
ACM Multimedia Systems Conference (MMSys) <6, 2015, Portland, OR, USA>
Although AR has a long history in the area of maintenance and service-support in industry, there still is a lack of lightweight, yet practical solutions for handheld AR systems in everyday workflows. Attempts to support complex maintenance tasks with AR still miss reliable tracking techniques, simple ways to be integrated into existing maintenance environments, and practical authoring solutions, which minimize costs for specialized content generation. We present a general, customisable application framework, allowing to employ AR and VR techniques in order to support technicians in their daily tasks. In contrast to other systems, we do not aim to replace existing support systems such as traditional manuals. Instead we integrate well-known AR- and novel presentation techniques with existing instruction media. To this end practical authoring solutions are crucial and hence we present an application development system based on web-standards such as HTML,CSS and X3D.
Design Factors for Flexible Capacitive Sensors in Ambient Intelligence
European Conference on Ambient Intelligence (AmI) <12, 2015, Athens, Greece>
Capacitive sensors in both touch and proximity varieties are becoming more common in many industrial and research applications. Each sensor requires one or more electrodes to create an electric field and measure changes thereof. The design and layout of those electrodes is crucial when designing applications and systems. It can influence range, detectable objects, or refresh rate. In the last years, new measurement systems and materials, as well as advances in rapid prototyping technologies have vastly increased the potential range of applications using flexible capacitive sensors. This paper contributes an extensive set of capacitive sensing measurements with different electrode materials and layouts for two measurement modes - self-capacitance and mutual capacitance. The evaluation of the measurement results reveals how well-suited certain materials are for different applications. We evaluate the characteristics of those materials for capacitive sensing and enable application designers to choose the appropriate material for their application.
Discriminative Shape from Shading in Uncalibrated Illumination
2015 IEEE Conference on Computer Vision and Pattern Recognition. Proceedings
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) <2015, Boston, MA, USA>
Estimating surface normals from just a single image is challenging. To simplify the problem, previous work focused on special cases, including directional lighting, known reflectance maps, etc., making shape from shading impractical outside the lab. To cope with more realistic settings, shading cues need to be combined and generalized to natural illumination. This significantly increases the complexity of the approach, as well as the number of parameters that require tuning. Enabled by a new large-scale dataset for training and analysis, we address this with a discriminative learning approach to shape from shading, which uses regression forests for efficient pixel-independent prediction and fast learning. Von Mises-Fisher distributions in the leaves of each tree enable the estimation of surface normals. To account for their expected spatial regularity, we introduce spatial features, including texton and silhouette features. The proposed silhouette features are computed from the occluding contours of the surface and provide scale-invariant context. Aside from computational efficiency, they enable good generalization to unseen data and importantly allow for a robust estimation of the reflectance map, extending our approach to the uncalibrated setting. Experiments show that our discriminative approach outperforms state-of-the-art methods on synthetic and real-world datasets.
Evaluating 3D Thumbnails for Virtual Object Galleries
Proceedings Web3D 2015
International Conference on 3D Web Technology (WEB3D) <20, 2015, Heraklion, Crete, Greece>
Virtual 3D object galleries on the Web nowadays often use realtime, interactive 3D graphics. However, this does usually still not hold for their preview images, sometimes referred to as thumbnails. We provide a technical analysis on the applicability of so-called 3D thumbnails within the context virtual 3D object galleries. Like a 2D thumbnail for an image, a 3D thumbnail acts as a compact preview for a real 3D model. In contrast to an image series, however, it enables a wider variety of interaction methods and rendering effects. By performing a case study, we show that such true 3D representations are, under certain circumstances, even able to outperform 2D image series in terms of bandwidth consumption. We thus present a complete pipeline for generating compact 3D thumbnails for given meshes in a fully automatic fashion.
Extended Surface Distance for Local Evaluation of 3D Medical Image Segmentations
The Visual Computer
Computer Graphics International (CGI) <32, 2015, Strasbourg, France>
The evaluation of 3D medical image segmentation quality requires a reliable detailed comparison of a reference segmentation with an automatic segmentation. It should be able to measure the quality accurately and, thus, to reveal problematic regions. While several (global) measures, providing a single quality value, are available, the only widely used local measure is the Surface Distance (i.e., point-to-surface distance). This measure, however, has significant drawbacks such as asymmetry and underestimation in distant and differently formed regions. Other available measures have limited suitability for 3D medical segmentation evaluation. We present a more reliable distance measure for assessing and analyzing local differences between automatic and reference (i.e., ground truth) 3D segmentations. We identify and overcome Surface Distance drawbacks, esp. in regions with larger dissimilarities. We evaluated our approach on four real medical image datasets. The results indicate that our measure provides more accurate local distance values.
From Information Assistance to Cognitive Automation: A Smart Assembly Use Case
Agents and Artificial Intelligence
International Conference on Agents and Artificial Intelligence (ICAART) <7, 2015, Lisbon, Portugal>
Information assistance helps in many application domains to structure, guide and control human work processes. However, it lacks a formalisation and automated processing of background knowledge which vice versa is required to provide ad-hoc assistance. In this paper, we describe our conceptual and technical work towards this cognitive automation. We focus here on including contextual background knowledge to raise the worker's awareness, guide, and monitor assembly activities. We present cognitive architectures as missing link between highly sophisticated manufacturing data systems and implicitly available contextual knowledge on work procedures and concepts of the work domain. Our work is illustrated with examples in SWI-Prolog and the Soar cognitive architecture which is part of the Plant@Hand assembly assistance system.
Fundamental Aspects for E-Government
Standards and Standardization
The upcoming initiatives using ICT in the government process should strengthen the benefit of e-government in most countries. Since e-government among other e-related terms is a widely (interpreted) term, it is sometimes challenging to understand the objective and goals of an initiative. Therefore, in this chapter, the authors introduce and explain most e-government related terms. Even more, they outline some interesting initiatives and implementations to explain the benefits of using ICT in the government domain. Concrete activities are aligned to the terms to explain their practical use in a better way. The authors conclude with several challenges that arise when thinking of the implementation of e-government services. Overall, this chapter should give a good overall view of e-government and the related issues.
Guiding the Exploration of Scatter Plot Data Using Motif-based Interest Measures
2015 Big Data Visual Analytics (BDVA)
IEEE International Symposium on Big Data Visual Analytics (BDVA) <1, 2015, Hobart, Australia>
Finding interesting patterns in large scatter plot spaces is a challenging problem and becomes even more difficult with increasing number of dimensions. Previous approaches for exploring large scatter plot spaces like e.g., the well-known Scagnostics approach, mainly focus on ranking scatter plots based on their global properties. However, often local patterns contribute significantly to the interestingness of a scatter plot. We are proposing a novel approach for the automatic determination of interesting views in scatter plot spaces based on analysis of local scatter plot segments. Specifically, we automatically classify similar local scatter plot segments, which we call scatter plot motifs. Inspired by the well-known tf ×idf-approach from information retrieval, we compute local and global quality measures based on certain frequency properties of the local motifs. We show how we can use these to filter, rank and compare scatter plots and their incorporated motifs. We demonstrate the usefulness of our approach with synthetic and real-world data sets and showcase our corresponding data exploration tool that visualizes the distribution of local scatter plot motifs in relation to a large overall scatter plot space.
2015 Digital Heritage International Congress. Volume 1
Digital Heritage International Congress (DH) <2015, Granada, Spain>
Isogeometric Analysis for Modelling and Design
Eurographics 2015. Short Papers
Annual Conference of the European Association for Computer Graphics (Eurographics) <36, 2015, Zürich, Switzerland>
We present an isogeometric design and analysis approach based on NURBS-compatible subdivision surfaces. The approach enables the description of watertight free-form surfaces of arbitrary degree, including conic sections and an accurate simulation and analysis based directly on the designed surface. To explore the seamless integration of design and analysis provided by the isogeometric approach, we built a prototype software which combines free-form modelling tools with thin shell simulation tools to offer the designer a wide range of design and analysis instruments.
MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering
IEEE Transactions on Visualization and Computer Graphics
Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and compare spatial situations (i.e., presence and flows of people at certain time moments) and to gain an understanding of the spatio-temporal changes (variations of situations over time). Traditional flow visualizations usually fail due to massive clutter. Modern approaches offer limited support for investigating the complex variation of the movements over longer time periods. We propose a visual analytics methodology that solves these issues by combined spatial and temporal simplifications. We have developed a graph-based method, called MobilityGraphs, which reveals movement patterns that were occluded in flow maps. Our method enables the visual representation of the spatio-temporal variation of movements for long time series of spatial situations originally containing a large number of intersecting flows. The interactive system supports data exploration from various perspectives and at various levels of detail by interactive setting of clustering parameters. The feasibility our approach was tested on aggregated mobility data derived from a set of geolocated Twitter posts within the Greater London city area and mobile phone call data records in Abidjan, Ivory Coast. We could show that MobilityGraphs support the identification of regular daily and weekly movement patterns of resident population.
New Constraints for Underwater Stereo Calibration
International Symposium on Image and Signal Processing and Analysis (ISPA) <9, 2015, Zagreb, Croatia>
In this paper we present new constraints for calibration of underwater stereo-camera-systems and 3Dreconstruction. These constraints are both intuitive and simple to realize. We show that additionally needed refractive parameters in such a system can be calibrated simultaneously. Our constraints partially build upon each other. A subset of them even enables the calibration from stereo-correspondences alone, making known calibration targets unnecessary.
Notes on Discrete Gaussian Scale Space.
Journal of Mathematical Imaging and Vision
Gaussian scale space is a well-known linear multi-scale representation for continuous signals. The exploration of its so-called deep structure by tracing critical points over scale has various theoretical applications and allows for the construction of a scale space hierarchy tree. However, implementation issues arise, caused by discretization and quantization errors. In order to develop more robust scale space based algorithms, the discrete nature of computer processed signals has to be taken into account. We propose suitable neighborhoods, boundary conditions, and sampling methods. In analogy to prevalent approaches and inspired by Lindeberg's scale space primal sketch, a discretized diffusion equation is derived, including requirements imposed by the chosen neighborhood and boundary condition. The resulting discrete scale space respects important topological invariants such as the Euler number, a key criterion for the successful implementation of algorithms operating on critical points in its deep structure. Relevant properties of the discrete diffusion equation and the Eigenvalue decomposition of its Laplacian kernel are discussed and a fast and robust sampling method is proposed. We finally discuss properties of topological graphs under the influence of smoothing, setting the stage for more robust deep structure extraction algorithms.
Opportunities for Activity Recognition using Ultrasound Doppler Sensing on Unmodified Mobile Phones
iWOAR 2015 - 2nd international Workshop on Sensor-based Activity Recognition and Interaction
International Workshop on Sensor-based Activity Recognition (iWOAR) <2, 2015, Rostock, Germany>
Nowadays activity recognition on smartphones is ubiquitously applied, for example to monitor personal health. The smartphone's sensors act as a foundation to provide information on movements, the user's location or direction. Incorporating ultrasound sensing using the smartphone's native speaker and microphone provides additional means for perceiving the environment and humans. In this paper, we outline possible usage scenarios for this new and promising sensing modality. Based on a custom implementation, we provide results on various experiments to assess the opportunities for activity recognition systems. We discuss various limitations and possibilities when wearing the smartphone on the human body. In stationary deployments, e.g. while placed on a night desk, our implementation is able to detect movements in proximities up to 2m as well as discern several gestures performed above the phone.
Pushing the Limits of 3D Color Printing: Error Diffusion with Translucent Materials
ACM Transactions on Graphics
Accurate color reproduction is important in many applications of 3D printing, from design prototypes to 3D color copies or portraits. Although full color is available via other technologies, multi-jet printers have greater potential for graphical 3D printing, in terms of reproducing complex appearance properties. However, to date these printers cannot produce full color, and doing so poses substantial technical challenges, from the shear amount of data to the translucency of the available color materials. In this article, we propose an error diffusion halftoning approach to achieve full color with multi-jet printers, which operates on multiple isosurfaces or layers within the object. We propose a novel traversal algorithm for voxel surfaces, which allows the transfer of existing error diffusion algorithms from 2D printing. The resulting prints faithfully reproduce colors, color gradients and fine-scale details.
Recent Developments in Material Microstructure: a Theory of Coarsening
MRS Online Proceedings Library
Symposium NN: Mathematical and Computational Aspects of Materials Science <2014, Boston, MA, USA>
Cellular networks are ubiquitous in nature. Most engineered materials are polycrystalline mi- crostructures composed of a myriad of small grains separated by grain boundaries, thus comprising cellular networks. The recently discovered grain boundary character distribution (GBCD) is an empirical distribution of the relative length (in 2D) or area (in 3D) of interface with a given lattice misorientation and normal. During the coarsening, or growth, process, an initially random grain boundary arrangement reaches a steady state that is strongly correlated to the interfacial energy density. In simulation, if the given energy density depends only on lattice misorientation, then the steady state GBCD and the energy are related by a Boltzmann distribution. This is among the simplest non-random distributions, corresponding to independent trials with respect to the energy. Why does such simplicity emerge from such complexity? Here we describe an entropy based theory which suggests that the evolution of the GBCD satisfies a Fokker-Planck Equation, an equation whose stationary state is a Boltzmann distribution.
Registering Images to Untextured Geometry Using Average Shading Gradients
2015 IEEE International Conference on Computer Vision
IEEE International Conference on Computer Vision (ICCV) <14, 2015, Santiago, Chile>
Many existing approaches for image-to-geometry registration assume that either a textured 3D model or a good initial guess of the 3D pose is available to bootstrap the registration process. In this paper we consider the registration of photographs to 3D models even when no texture information is available. This is very challenging as we cannot rely on texture gradients, and even shading gradients are hard to estimate since the lighting conditions are unknown. To that end, we propose average shading gradients, a rendering technique that estimates the average gradient magnitude over all lighting directions under Lambertian shading. We use this gradient representation as the building block of a registration pipeline based on matching sparse features. To cope with inevitable false matches due to the missing texture information and to increase robustness, the pose of the 3D model is estimated in two stages. Coarse pose hypotheses are first obtained from a single correct match each, subsequently refined using SIFT flow, and finally verified. We apply our algorithm to registering images of real-world objects to untextured 3D meshes of limited accuracy.
The Visual Exploration of Aggregate Similarity for Multi-dimensional Clustering
IVAPP 2015. Proceedings
International Conference on Information Visualization Theory and Applications (IVAPP) <6, 2015, Berlin, Germany>
We present a visualisation prototype for the support of a novel approach to clustering called TRIAGE. TRIAGE uses aggregation functions which are more adaptable and flexible than the weighted mean for similarity modelling. While TRIAGE has proven itself in practice, the use of complex similarity models makes the interpretation of TRIAGE clusterings challenging. We address this challenge by providing analysts with a linked, matrix-based visualisation of all relevant data attributes. We employ data sampling and matrix seriation to support both effective overviews and fluid, interactive exploration using the same visual metaphor for heterogeneous attributes. The usability of our prototype is demonstrated and assessed with the help of real-world usage scenarios from the cyber-security domain.
Tiled Projection Onto Deforming Screens
Computer Graphics and Visual Computing
Computer Graphics and Visual Computing (CGVC) <2015, London, UK>
For the next generation of visual installations it will not be sufficient to surround the visitor by stunning responsive audiovisual experiences - the next step is that space itself deforms in response to the user or user groups. Dynamic reconfigurable spaces are a new exciting possibility to influence the behaviour of groups and individuals; they may have the potential of stimulating various different social interactions and behaviours in a user-adapted fashion. However, some technical hurdles must be overcome. Projecting on larger surfaces, like a ceiling screen of 6 x 8 meters, is typically possible only with a tiled projection, i.e., with multiple projectors creating one large seamless image. This works well with a static ceiling; however, when the ceiling dynamically moves and deforms, the tiling becomes visible since the images no longer match. In this paper we present a method that can avoid such artifacts by dynamically adjusting the tiled projection to the deforming surface. Our method is surprisingly simple and efficient, and it does not require any image processing at runtime, nor any 3D reconstruction of the surface at any point.
Video Segmentation via a Gaussian Switch Background Model and Higher Order Markov Random Fields
VISAPP 2015 - Volume I
International Conference on Computer Vision Theory and Applications (VISAPP) <10, 2015, Berlin, Germany>
Foreground-background segmentation in videos is an important low-level task needed for many different applications in computer vision. Therefore, a great variety of different algorithms have been proposed to deal with this problem, however none can deliver satisfactory results in all circumstances. Our approach combines an efficient novel Background Substraction algorithm with a higher order Markov Random Field (MRF) which can model the spatial relations between the pixels of an image far better than a simple pairwise MRF used in most of the state of the art methods. Afterwards, a runtime optimized Belief Propagation algorithm is used to compute an enhanced segmentation based on this model. Lastly, a local between Class Variance method is combined with this to enrich the data from the Background Substraction. To evaluate the results the difficult Wallflower data set is used.
VisInfo: A Digital Library System for Time Series Research Data Based on Exploratory Search - a User-centered Design Approach
International Journal on Digital Libraries
To this day, data-driven science is a widely accepted concept in the digital library (DL) context (Hey et al. in The fourth paradigm: data-intensive scientific discovery. Microsoft Research, 2009). In the same way, domain knowledge from information visualization, visual analytics, and exploratory search has found its way into the DL workflow. This trend is expected to continue, considering future DLchallenges such as content-based access to newdocument types, visual search, and exploration for information landscapes, or big data in general. To cope with these challenges, DL actors need to collaborate with external specialists from different domains to complement each other and succeed in given tasks such as making research data publicly available. Through these interdisciplinary approaches, the DL ecosystem may contribute to applications focused on data-driven science and digital scholarship. In this work, we present Vis- Info (2014) , a web-based digital library system (DLS) with the goal to provide visual access to time series research data. Based on an exploratory search (ES) concept (White and Roth in Synth Lect Inf Concepts Retr Serv 1(1):1-98, 2009), VisInfo at first provides a content-based overview visualization of large amounts of time series research data. Further, the system enables the user to define visual queries by example or by sketch. Finally, VisInfo presents visual-interactive capability for the exploration of search results. The development process of VisInfo was based on the user-centered design principle. Experts from computer science, a scientific digital library, usability engineering, and scientists from the earth, and environmental sciences were involved in an interdisciplinary approach. We report on comprehensive user studies in the requirement analysis phase based on paper prototyping, user interviews, screen casts, and user questionnaires. Heuristic evaluations and two usability testing rounds were applied during the system implementation and the deployment phase and certify measurable improvements for our DLS. Based on the lessons learned in VisInfo, we suggest a generalized project workflow that may be applied in related, prospective approaches.
Weighted Integration of Neighbors Distance Ratio in Multi-biometric Fusion
Annual International Conference of the Biometrics Special Interest Group (BIOSIG) <14, 2015, Darmstadt, Germany>
This work presents an approach to integrate biometric source weighting in the calculation of neighbors distance ratios to be used within a classification-based multi-biometric fusion process. The neighbors distance ratio represents the elevation of the top ranked identification match to the following ranks. Using biometric source weighing can help achieve more accurate initial identity ranking necessary for neighbors distance ratios. It also influences the effect of each biometric source on the ratios values. The proposed approach is developed and evaluated using the Biometric Scores Set BSSR1 database. The results are presented in the verification scenario as receiver operating curves (ROC). The achieved performance is compared to a number of baseline solutions and a satisfying and stable performance was achieved with a clear benefit of integrating the biometric source weights.