Armin Pobitzer

PhD student

Publications

2014

    [DOI] [Bibtex]
    @INCOLLECTION {peikert2014comparison,
    author = "Ronald Peikert and Armin Pobitzer and Filip Sadlo and Benjamin Schindler",
    title = "A Comparison of Finite-Time and Finite-Size Lyapunov Exponents",
    booktitle = "Topological Methods in Data Analysis and Visualization III",
    publisher = "Springer International Publishing",
    year = "2014",
    editor = "Peer-Timo Bremer and Ingrid Hotz and Valerio Pascucci and Ronald Peikert",
    series = "Mathematics and Visualization",
    pages = "187--200",
    images = "images/peikert2014comparison.png",
    thumbnails = "images/peikert2014comparison_thumb.png",
    doi = "10.1007/978-3-319-04099-8_12",
    url = "http://dx.doi.org/10.1007/978-3-319-04099-8_12",
    isbn = "978-3-319-04098-1"
    }

2012

    [PDF] [DOI] [Bibtex]
    @INPROCEEDINGS {Pobitzer12Filtering,
    author = "Armin Pobitzer and Ronald Peikert and Raphael Fuchs and Holger Theisel and Helwig Hauser",
    title = "Filtering of FTLE for Visualizing Spatial Separation in Unsteady 3D Flow",
    booktitle = "Topological Methods in Data Analysis and Visualization II",
    year = "2012",
    editor = "R. Peikert and H. Hauser and H. Carr and R. Fuchs",
    pages = "237--253",
    publisher = "Springer",
    abstract = "Texture mapping is a common method for combining surface geometry with image data, with the resulting photorealistic 3D models being suitable not only for visualisation purposes but also for interpretation and spatial measurement, in many application fields, such as cultural heritage and the earth sciences. When acquiring images for creation of photorealistic models, it is usual to collect more data than is finally necessary for the texturing process. Images may be collected from multiple locations, sometimes with different cameras or lens configurations and large amounts of overlap may exist. Consequently, much redundancy may be present, requiring sorting to choose the most suitable images to texture the model triangles. This paper presents a framework for visualization and analysis of the geometric relations between triangles of the terrain model and covering image sets. The application provides decision support for selection of an image subset optimized for 3D model texturing purposes, for non-specialists. It aims to improve the communication of geometrical dependencies between model triangles and the available digital images, through the use of static and interactive information visualisation methods. The tool was used for computer-aided selection of image subsets optimized for texturing of 3D geological outcrop models. The resulting textured models were of high quality and with a minimum of missing texture, and the time spent in time-consuming reprocessing was reduced. Anecdotal evidence indicated that an increased user confidence in the final textured model quality and completeness makes the framework highly beneficial. ",
    pdf = "pdfs/Pobitzer12Filtering.pdf",
    images = "images/Pobitzer12Filtering01.png, images/Pobitzer12Filtering02.png",
    thumbnails = "images/Pobitzer12Filtering01_thumb.png, images/Pobitzer12Filtering02_thumb.png",
    doi = "http://dx.doi.org/10.1007/978-3-642-23175-9_16",
    url = "http://dx.doi.org/10.1007/978-3-642-23175-9_16",
    project = "semseg"
    }
    [PDF] [Bibtex]
    @MISC {Brambilla12Geilo,
    author = "Andrea Brambilla and Armin Pobitzer and Helwig Hauser",
    title = "Flow Visualization and the SemSeg project",
    howpublished = "Poster presented at the Sintef winter school 2012",
    month = "January",
    year = "2012",
    pdf = "pdfs/Brambilla12Geilo.pdf",
    images = "images/Brambilla12Geilo01.png",
    thumbnails = "images/Brambilla12Geilo01_thumb.png",
    location = "Geilo, Norway",
    url = "http://www.sintef.no/Projectweb/eVITA/Winter-Schools/2012/"
    }
    [Bibtex]
    @MISC {Pobitzer12Exploiting,
    author = "Armin Pobitzer",
    title = "Exploiting the Turbulence Energy Cascade for Flow Visualization",
    howpublished = "Invited talk at the weekly seminar of Laboratoire de M\'{e}canique de Lille",
    month = "February",
    year = "2012",
    abstract = "Even though modern technology and tools, together with available computer power, theoretically enable us to visualise large vector fields directly, it often is neither interesting nor necessary to visualise every detail of them. Usually, interesting features of the investigated field can be visualized more efficiently using dedicated feature detectors, e.g. the $\lambda_2$ criterion [2] for vertical structures. In settings with highly complex flow patterns, such as fully developed turbulence, feature detectors may, however, mark almost the whole flow domain as a feature. In these cases visualisations based on these detectors become hard to interpret due to occlusion and visual cluttering. This problem is well known in visualisation, and has been addressed by previous work. Many of these methods have in common that they extract all features at first, and discard some of them afterwards. Criteria for this discarding are often of geometrical character, such as size (volume, length, area ...) or distance to next feature. While the visual output of such strategies satisfies the need to reduce occlusion and visual clutter, the interpretability of the results remains an open question. The immediate relation between the velocity field and the output of the feature detector is lost, since the simplication is made on the `image-level' only. In this talk we discuss how the internal structure of flow fields can be exploited, in particular the turbulence energy cascade. Based on proper orthogonal decomposition [3], we present a general simplification scheme for feature extraction that preserves the 1-to-1 relation between visual output of the method and the flow pattern it is extracted from. We apply the simplification scheme on both Eulerian and Lagrangian feature detectors and discuss the results. In particular the impact of the simplification scheme on the detection and visualization of Lagrangian Coherent Structures based on Finite-time Lyapunov exponents is addressed. The results presented in this talk are published in the article `Energy-scale Aware Feature Extraction for Flow Visualization [4]. [1] L. Hesselink, J. Helman, and P. Ning, Quantitative image processing in fluid mechanics, Experimental Thermal and Fluid Science, 5 (1992), pp. 605-616. Special Issue on Experimental Methods in Thermal and Fluid Science. [2] J. Jeong and F. Hussain, On the identification of a vortex, Journal of Fluid Mechanics, 285 (1995), pp. 69-84. [3] J. L. Lumley, The structure of inhomogeneous turbulent flows, in Atmospheric Turbulence and Radio Wave Propagation, Elsevier, 1967, pp. 166-178. [4] A. Pobitzer, M. Tutkun, O Andreassen, R. Fuchs, R. Peikert, and H. Hauser, Energy-scale aware feature extraction for flow visualization, Computer Graphics Forum, 30 (2011), pp. 771-780. [5] F. Sadlo and R. Peikert, Visualizing Lagrangian coherent structures: A comparison to vector field topology, in Topology-Based Methods in Visualization II: Proc. of the 2nd TopoInVis Workshop (TopoInVis 2007), H.-C. Hege, K. Polthier, and G. Scheuermann, eds, 2009, pp. 15-29.",
    images = "images/no_thumb.png",
    thumbnails = "images/no_thumb.png",
    location = "Lille, France",
    url = "http://lml.univ-lille1.fr/lml/?page=33\&seminID=172"
    }
    [PDF] [Bibtex]
    @MISC {Pobitzer12Physics,
    author = "Armin Pobitzer",
    title = "Physics-based Velocity Field Simplification for Flow Visualization",
    howpublished = "Invited talk at Minisymposium on Analysis and Representation of Large Data Sets",
    month = "February",
    year = "2012",
    abstract = "With the availability of more computing power, simulations of increasingly complex fluid flows have become possible. In the attempt to make sense of data, visualization has greatly gained importance in everyday scientific computing. Many visualization techniques do, however, suffer from a tendency to overly rich response in complex scenarios. Hence, filtering of the visual output is an important topic. In this talk we discuss how such filtering can be achieved in a physically meaningful way, giving examples from the extraction of vortices and Lagrangian coherent structures.",
    pdf = "pdfs/Pobitzer12Physics.pdf",
    images = "images/Pobitzer12Physics.png",
    thumbnails = "images/Pobitzer12Physics_thumb.png",
    location = "Madrid, Spain"
    }
    [DOI] [Bibtex]
    @ARTICLE {Schindler12Lagrangian,
    author = "Benjamin Schindler and Raphael Fuchs and Stefan Barp and Jurgen Waser and Armin Pobitzer and Robert Carnecky and Kresimir Matkovic and Ronald Peikert",
    title = "Lagrangian Coherent Structures for Design Analysis of Revolving Doors",
    journal = "Visualization and Computer Graphics, IEEE Transactions on",
    year = "2012",
    volume = "18",
    number = "12",
    pages = "2159--2168",
    month = "December",
    abstract = "Room air flow and air exchange are important aspects for the design of energy-efficient buildings. As a result, simulations are increasingly used prior to construction to achieve an energy-efficient design. We present a visual analysis of air flow generated at building entrances, which uses a combination of revolving doors and air curtains. The resulting flow pattern is challenging because of two interacting flow patterns: On the one hand, the revolving door acts as a pump, on the other hand, the air curtain creates a layer of uniformly moving warm air between the interior of the building and the revolving door. Lagrangian coherent structures (LCS), which by definition are flow barriers, are the method of choice for visualizing the separation and recirculation behavior of warm and cold air flow. The extraction of LCS is based on the finite-time Lyapunov exponent (FTLE) and makes use of a ridge definition which is consistent with the concept of weak LCS. Both FTLE computation and ridge extraction are done in a robust and efficient way by making use of the fast Fourier transform for computing scale-space derivatives.",
    images = "images/Schindler12Lagrangian01.png",
    thumbnails = "images/Schindler12Lagrangian01_thumb.png",
    doi = "10.1109/TVCG.2012.243",
    issn = "1077-2626",
    url = "http://visdom.at/person/5/"
    }
    [PDF] [Bibtex]
    @PHDTHESIS {pobitzer12thesis,
    author = "Armin Pobitzer",
    title = "Interactive Visual Analysis of Time-dependent Flows: Physics- and Statistics-based Semantics",
    school = "Department of Informatics, University of Bergen, Norway",
    year = "2012",
    month = "Apr",
    abstract = "With the increasing use of numerical simulations in the fluid mechanics community in recent years flow visualization increasingly gains importance as an advanced analysis tool for the simulation output. Up to now, flow visualization has mainly focused on the extraction and visualization of structures that are defined by their semantic meaning. Examples for such structures are vortices or separation structures between different groups of particles that travel together. In order to deepen our understanding of structures linked to certain flow phenomena, e.g., how and why they appear, evolve, and finally are destroyed, also linking structures to semantic meaning that is not attributed to them by their very definition, is a highly promising research direction to pursue. In this thesis we provide several approaches on how to augment structures stemming from classical flow visualization techniques by additional semantic information originating from new methods based on physics and statistics. In particular, we target separation structures, the linking of structures with a local semantics to global flow phenomena, and minimal representation of particle dynamics in the context of path line attributes.",
    pdf = "pdfs/pobitzer12thesis.pdf",
    images = "images/Pobitzer12Physics.png",
    thumbnails = "images/Pobitzer12Physics_thumb.png",
    isbn = "978-82-308-2063-6",
    url = "https://bora.uib.no/handle/1956/5856"
    }
    [PDF] [Bibtex]
    @MISC {Pobitzer12NceSubsea,
    author = "Armin Pobitzer",
    title = "The State of the Art in Flow Visualization",
    howpublished = "Invited talk at NCS Subsea Theme Meeting - Visualization for Industrial Applications",
    month = "February",
    year = "2012",
    pdf = "pdfs/Pobitzer12NceSubsea.pdf",
    images = "images/no_thumb.png",
    thumbnails = "images/no_thumb.png",
    location = "Bergen, Norway",
    url = "http://eng.ncesubsea.no/page/389/activity/1029/theme-meeting-visualization-for-industrial-applications"
    }
    [Bibtex]
    @MISC {Pobitzer12PacificVisTutorial,
    author = "Helwig Hauser and Alexander Kuhn and Armin Pobitzer and Maik Schulze",
    title = "Time-Dependent Flow Visualization",
    howpublished = "Tutorial at 5th IEEE PacificVis Symposium",
    month = "February",
    year = "2012",
    abstract = "Vector fields are a common representation of many kinds of dynamic phenomena in a large variety of application fields. A particularly interesting class of vector fields represent time-dependent flows, i.e., flows where the vectors change over time themselves. A lot of good and relevant research work has been done on the question of how to visualize such unsteady vector fields and an overview is presented in this tutorial. In particularly, we emphasize Lagrangian methods, space-time domain approaches, and interactive visual analysis as three interesting and promising types of methodology. The tutorial is also introduced with some general remarks, in particular also on the question of why it often is not straight forward to extend methods that originally were developed for steady flows to the domain of unsteady flows. A number of examples illustrate the overview.",
    images = "images/Pobitzer12PacificVisTutorial.png",
    thumbnails = "images/Pobitzer12PacificVisTutorial_thumb.png",
    location = "Songdo, South Korea",
    url = "http://www.semseg.eu/download/2012-02-28--TimeDepFlowVizTutorial--materials/"
    }
    [PDF] [Bibtex]
    @INPROCEEDINGS {Pobitzer12AStatistics,
    author = "Armin Pobitzer and Alan Lez and Kresimir Matkovic and Helwig Hauser",
    title = "A Statistics-based Dimension Reduction of the Space of Path Line Attributes for Interactive Visual Flow Analysis",
    booktitle = "Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2012)",
    year = "2012",
    pages = "113--120",
    month = "March",
    abstract = "Recent work has shown the great potential of interactive flow analysis by the analysis of path lines. The choice of suitable attributes, describing the path lines, is, however, still an open question. This paper addresses this question performing a statistical analysis of the path line attribute space. In this way we are able to balance the usage of computing power and storage with the necessity to not loose relevant information. We demonstrate how a carefully chosen attribute set can improve the benefits of state-of-the art interactive flow analysis. The results obtained are compared to previously published work.",
    pdf = "pdfs/Pobitzer12AStatistics.pdf",
    images = "images/Pobitzer12AStatistics.png",
    thumbnails = "images/Pobitzer12AStatistics_thumb.png",
    location = "Songdo, Korea"
    }

2011

    [Bibtex]
    @ARTICLE {pobitzer11topology,
    author = "Armin Pobitzer and Ronald Peikert and Raphael Fuchs and Benjamin Schindler and Alexander Kuhn and Holger Theisel and Kresimir Matkovic and Helwig Hauser",
    title = "The State of the Art in Topology-based Visualization of Unsteady Flow",
    journal = "Computer Graphics Forum",
    year = "2011",
    volume = "30",
    number = "6",
    pages = "1789--1811",
    month = "September",
    abstract = "Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analyzing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available.We give an overview of previous research leading towards topology-based and topology-inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e., steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space-time domain approaches, local methods, and stochastic and multi-field approaches. Furthermore, we illustrate our review with practical examples for the different approaches.",
    images = "images/pobitzer10topology.jpg,",
    thumbnails = "images/pobitzer10topology_thumb.jpg",
    project = "semseg",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2011.01901.x"
    }
    [Bibtex]
    @ARTICLE {pobitzer11energyScale,
    author = "Armin Pobitzer and Murat Tutkun and {\O }yvind Andreassen and Raphael Fuchs and Ronald Peikert and Helwig Hauser",
    title = "Energy-scale Aware Feature Extraction for Flow Visualization",
    journal = "Computer Graphics Forum",
    year = "2011",
    volume = "30",
    number = "3",
    pages = "771--780",
    abstract = "In the visualization of flow simulation data, feature detectors often tend to result in overly rich response, making some sort of filtering or simplification necessary to convey meaningful images. In this paper we present an approach that builds upon a decomposition of the flow field according to dynamical importance of different scales of motion energy. Focusing on the high-energy scales leads to a reduction of the flow field while retaining the underlying physical process. The presented method acknowledges the intrinsic structures of the flow according to its energy and therefore allows to focus on the energetically most interesting aspects of the flow. Our analysis shows that this approach can be used for methods based on both local feature extraction and particle integration and we provide a discussion of the error caused by the approximation. Finally, we illustrate the use of the proposed approach for both a local and a global feature detector and in the context of numerical flow simulations.",
    images = "images/pobitzer11energyScale1.jpg, images/pobitzer11energyScale3.jpg, images/pobitzer11energyScale2.jpg",
    thumbnails = "images/pobitzer11energyScale1_thumb.jpg, images/pobitzer11energyScale3_thumb.jpg, images/pobitzer11energyScale2_thumb.jpg",
    url = "http://dx.doi.org/10.1111/j.1467-8659.2011.01926.x",
    event = "EuroVis 2011",
    location = "Bergen, Norway",
    project = "semseg"
    }
    [DOI] [Bibtex]
    @ARTICLE {Matkovic11CurrentTrends,
    author = "Kresimir Matkovic and Alan Lez and Helwig Hauser and Armin Pobitzer and Holger Theisel and Alexander Kuhn and Mathias Otto and Ronald Peikert and Benjamin Schindler and Raphael Fuchs",
    title = "Current Trends for 4D Space-Time Topology for Semantic Flow Segmentation",
    journal = "Procedia Computer Science",
    year = "2011",
    volume = "7",
    number = "0",
    pages = "253--255",
    abstract = "Recent advances in computing and simulation technology promote the simulation of time-dependent flows, i.e., flows where the velocity field changes over time. The simulation of time-dependent flow is a more realistic approximation of natural phenomena and it represents an invaluable tool for scientists and practitioners in multiple disciplines, including meteorology, vehicle design, and medicine. Flow visualization, a subfield of scientific visualization, is one of several research areas which deal with the analysis of flows. There are many methods for the analysis of steady flows, but the extension to the time-dependent case is not straight forward. The SemSeg project, a FET-Open project in the 7th Framework programme, attempts to provide a solution for the semantic segmentation of time-dependent flows. It aims at the formulation of a sound theoretical mechanism to describe structural features in time-dependent flow. In this paper, we briefly summarize recent research results from the SemSeg project. Several different approaches are pursued in the project, including methods based on the finite-time Lyapunov exponent (FTLE), methods based on vector field topology (VFT), and interactive visual analysis (IVA) methods. Uncertainty visualization and the interactive evaluation of methods are helping in evaluating the results.",
    images = "images/Matkovic11CurrentTrends.png",
    thumbnails = "images/Matkovic11CurrentTrends_thumb.png",
    note = "Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11)",
    issn = "1877-0509",
    doi = "10.1016/j.procs.2011.09.013",
    url = "http://www.sciencedirect.com/science/article/pii/S1877050911005734"
    }
    [Bibtex]
    @INPROCEEDINGS {lez11pathlines,
    author = "Alan Lez and Andreas Zajic and Kresimir Matkovic and Armin Pobitzer and Michael Mayer and Helwig Hauser",
    title = "Interactive Exploration and Analysis of Pathlines in Flow Data",
    booktitle = "Proc. International Conference in Central Europe on ComputerGraphics, Visualization and Computer Vision (WSCG 2011)",
    year = "2011",
    pages = "17--24",
    abstract = "The rapid development of large-scale scientific computing nowadays allows to inherently respect the unsteady character of natural phenomena in computational flow simulation. With this new trend to more regularly consider time-dependent flow scenarios, an according new need for advanced exploration and analysis solutions emerges. In this paper, we now present three new concepts in pathline analysis which further improve the abilities of analysis: a multi-step analysis which helps to save time and space needed for computation, direct pathline brushing, and usage of pre-configured view arrangements. We have found that clever combining of these three concepts with already existing methods creates very powerful tool for pathline analysis. The coordinated multiple views (CMV) tool used supports iterative composite brushing which enables a quick information drill-down. We illustrate the usefulness using an example from the automotive industry. We have analyzed an exhaust manifoldtime-dependent simulation data set.",
    images = "images/lez11pathlines1.jpg, images/lez11pathlines2.jpg",
    thumbnails = "images/lez11pathlines1_thumb.jpg, images/lez11pathlines2_thumb.jpg",
    location = "Plzen, Czech Republic",
    project = "semseg"
    }
    [Bibtex]
    @INPROCEEDINGS {pobitzer11semseg,
    author = "Armin Pobitzer and Helwig Hauser",
    title = "The {SemSeg} project and recent developments in flow visualization",
    booktitle = "Proc. Sixth National Conference on Computational Mechanics (MekIT'11)",
    year = "2011",
    pages = "281--292",
    address = "Trondheim, Norway",
    month = "May",
    publisher = "Tapir Academic Press",
    abstract = "The present paper discusses recent efforts to develop semantic segmentation of spacetime flow domains for visualization purposes, taking thework of the SemSeg project as a starting point. In particular we address separation structures based on Finite-time Lyapunov exponents and their extraction, the incorporation of uncertainty, and the application of Interactive Visual Analysis in the context of flow visualization.",
    images = "images/pobitzer11semseg.jpg",
    thumbnails = "images/pobitzer11semseg_thumb.jpg",
    editors = "B. Skallerud and H.I. Andersson",
    project = "semseg"
    }

2010

    [Bibtex]
    @INPROCEEDINGS {pobitzer10topology,
    author = "Armin Pobitzer and Ronald Peikert and Raphael Fuchs and Benjamin Schindler and Alexander Kuhn and Holger Theisel and Kresimir Matkovic and Helwig Hauser",
    title = "On the Way Towards Topology-Based Visualization of Unsteady Flow - the State of the Art",
    booktitle = "EuroGraphics 2010 State of the Art Reports (STARs)",
    year = "2010",
    pages = "137--154",
    abstract = "Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Topology-based methods have shown their convenience for visualizing and analyzing steady flow but a counterpart for unsteady flow is still missing. However, a lot of good and relevant work has been done aiming at such a solution.We give an overview of the research done on the way towards topology-based visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, takingclassical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian Methods, Space-Time Domain Approaches, Local Methods, and Stochastic and Multi-Field Approaches. Furthermore, weillustrated our review with practical examples for the different approaches.",
    images = "images/pobitzer10topology.jpg,",
    thumbnails = "images/pobitzer10topology_thumb.jpg",
    event = "EuroGraphics 2010",
    location = "Norrk{\"o}ping, Sweden",
    pres = "pdfs/pobitzer10topology-presentation.pdf",
    project = "semseg"
    }