Liste der Publikationen
A Visual-Interactive System for Prostate Cancer Cohort Analysis
IEEE Computer Graphics and Applications, Vol.35 (2015), 3, pp. 44-55
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.
Pushing the Limits of 3D Color Printing: Error Diffusion with Translucent Materials
ACM Transactions on Graphics, Vol.35 (2015), 1, Article 4, 13 p.
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.
Content First - A concept for Industrial Augmented Reality Maintenance Applications using Mobile Devices
ACM SIGMM: MMSys '15 : Proceedings of the 6th ACM Multimedia Systems Conference. New York: ACM, 2015, pp. 105-111
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.
Ambient Intelligence from Senior Citizens' Perspectives: Understanding Privacy Concerns, Technology Acceptance, and Expectations
Ruyter, Boris de (Ed.) et al.: Ambient Intelligence : 12th European Conference, AmI 2015. Springer, 2015. (Lecture Notes in Computer Science (LNCS) 9425), pp. 48-59
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.
A Modular Software Architecture for Processing of Big Geospatial Data in the Cloud
Computers & Graphics, Vol.49 (2015), pp. 69-81
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.
MobilityGraphs: Visual Analysis of Mass Mobility Dynamics via Spatio-Temporal Graphs and Clustering
IEEE Transactions on Visualization and Computer Graphics, Vol.22 (2015), 1, pp. 11-20
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.
Botential: Localizing On-Body Gestures by Measuring Electrical Signatures on the Human Skin
Association for Computing Machinery (ACM): MobileHCI 2015 : Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services. New York: ACM, 2015, pp. 207-216
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.
Notes on Discrete Gaussian Scale Space.
Journal of Mathematical Imaging and Vision, Vol.51 (2015), 1, pp. 106-123
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.
An Adaptive Acceleration Structure for Screen-space Ray Tracing
Doggett, Michael (Ed.) et al.: Proceedings of the 7th Conference on High-Performance Graphics 2015. New York: ACM, 2015, pp. 67-76
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.