Liste der Publikationen
Gewinner und die Publikationen, die in die engere Wahl gekommen sind.
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.
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.
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.
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.
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.
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.