Fachbereich 6 Mathematik/Informatik

Institut für Informatik


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Haunert, Jan-Henrik, Prof. Dr.-Ing.

Prof. Dr.-Ing. Jan-Henrik Haunert

Universität Osnabrück
Institut für Informatik
Arbeitsgruppe Geoinformatik
Barbarastr. 22b
49076 Osnabrück

Raum: 92/105
Tel.: +49 541 969-3964
Fax.: +49 541 969-3939
E-Mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it.

Sprechzeiten:

Do von 14-15 Uhr (Vorlesungszeit) oder nach Vereinbarung

Aufgaben

  • Professor für Geoinformatik
  • Leiter des Arbeitskreises Geoinformatik der Deutschen Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation e.V. (DGPF)

Lehre im Sommersemester 2016 (abgeschlossene Lehre)

Forschungsschwerpunkte

Werdegang

Preise

wichtige Publikationen  (vollständige Liste nach Typ und nach Jahr)

  1. M Chimani, T C Dijk and J -H Haunert.
    How to Eat a Graph: Computing Selection Sequences for the Continuous Generalization of Road Networks.
    In Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM-GIS'14). 2014, 243–252. URL, DOI BibTeX

    @inproceedings{ChimaniEtAl2014,
    	author = "M. Chimani and T. C. van Dijk and J.-H. Haunert",
    	booktitle = "Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM-GIS'14)",
    	doi = "10.1145/2666310.2666414",
    	pages = "243--252",
    	title = "How to Eat a Graph: Computing Selection Sequences for the Continuous Generalization of Road Networks",
    	url = "http://www.igf.uni-osnabrueck.de/images/dateien/haunert/eatgraph.pdf",
    	year = 2014
    }
    
  2. A Gemsa, J -H Haunert and M Nöllenburg.
    Multirow Boundary-Labeling Algorithms for Panorama Images.
    ACM Transations on Spatial Algorithms and Systems 1(1):1–30, 2015. DOI BibTeX

    @article{DBLP:journals/tocs/GemsaHN15,
    	author = {A. Gemsa and J.{-}H. Haunert and M. N{\"{o}}llenburg},
    	doi = "10.1145/2794299",
    	journal = "{ACM} Transations on Spatial Algorithms and Systems",
    	number = 1,
    	pages = "1--30",
    	title = "Multirow Boundary-Labeling Algorithms for Panorama Images",
    	volume = 1,
    	year = 2015
    }
    
  3. M Fink, J -H Haunert, A Schulz, J Spoerhase and A Wolff.
    Algorithms for Labeling Focus Regions.
    IEEE Transactions on Visualization and Computer Graphics (Proc. Information Visualization 2012) 18(12):2583–2592, 2012. PDF BibTeX

    @article{FinkEtAl2012,
    	abstract = "In this paper, we investigate the problem of labeling point sites in focus regions of maps or diagrams. This problem occurs, for example, when the user of a mapping service wants to see the names of restaurants or other POIs in a crowded downtown area but keep the overview over a larger area. Our approach is to place the labels at the boundary of the focus region and connect each site with its label by a linear connection, which is called a leader. In this way, we move labels from the focus region to the less valuable context region surrounding it. In order to make the leader layout well readable, we present algorithms that rule out crossings between leaders and optimize other characteristics such as total leader length and distance between labels. \par This yields a new variant of the boundary labeling problem, which has been studied in the literature. Other than in traditional boundary labeling, where leaders are usually schematized polylines, we focus on leaders that are either straight-line segments or B\'ezier curves. Further, we present algorithms that, given the sites, find a position of the focus region that optimizes the above characteristics. \par We also consider a variant of the problem where we have more sites than space for labels. In this situation, we assume that the sites are prioritized by the user. Alternatively, we take a new facility-location perspective which yields a clustering of the sites. We label one representative of each cluster. If the user wishes, we apply our approach to the sites within a cluster, giving details on demand.",
    	author = "Fink, M. and Haunert, J.-H. and Schulz, A. and Spoerhase, J. and Wolff, A.",
    	journal = "IEEE Transactions on Visualization and Computer Graphics (Proc. Information Visualization 2012)",
    	number = 12,
    	pages = "2583--2592",
    	pdf = "http://www1.informatik.uni-wuerzburg.de/pub/fink/paper/fhssw-alfr-InfoVis12.pdf",
    	timestamp = "2013-03-13T10:23:34.000+0100",
    	title = "Algorithms for Labeling Focus Regions",
    	volume = 18,
    	year = 2012
    }
    
  4. M Fink, J -H Haunert, J Spoerhase and A Wolff.
    Selecting the Aspect Ratio of a Scatter Plot Based on Its Delaunay Triangulation.
    IEEE Transactions on Visualization and Computer Graphics (Proc. Information Visualization 2013) 19(12):2326–2335, 2013. BibTeX

    @article{FinkEtAl2013b,
    	author = "Fink, M. and Haunert, J.-H. and Spoerhase, J. and Wolff, A.",
    	journal = "IEEE Transactions on Visualization and Computer Graphics (Proc. Information Visualization 2013)",
    	number = 12,
    	pages = "2326--2335",
    	timestamp = "2013-07-25T18:19:08.000+0200",
    	title = "Selecting the Aspect Ratio of a Scatter Plot Based on Its {D}elaunay Triangulation",
    	volume = 19,
    	year = 2013
    }
    
  5. J -H Haunert and M Sester.
    Area collapse and road centerlines based on straight skeletons.
    GeoInformatica 12(2):169–191, 2008. URL PDF BibTeX

    @article{haunert2008,
    	abstract = "Skeletonization of polygons is a technique, which is often applied to problems of cartography and geographic information science. Especially it is needed for generalization tasks such as the collapse of small or narrow areas, which are negligible for a certain scale. Different skeleton operators can be used for such tasks. One of them is the straight skeleton, which was rediscovered by computer scientists several years ago after decades of neglect. Its full range of practicability and its benefits for cartographic applications have not been revealed yet. Based on the straight skeleton an area collapse that preserves topological constraints as well as a partial area collapse can be performed. An automatic method for the derivation of road centerlines from a cadastral dataset, which uses special characteristics of the straight skeleton, is shown.",
    	author = "Haunert, J.-H. and Sester, M.",
    	journal = "GeoInformatica",
    	number = 2,
    	pages = "169--191",
    	pdf = "http://www1.informatik.uni-wuerzburg.de/pub/haunert/pdf/HaunertSester2008.pdf",
    	timestamp = "2011-11-07T12:01:04.000+0100",
    	title = "Area collapse and road centerlines based on straight skeletons",
    	url = "http://www.springerlink.com/content/20103w9530887286/",
    	volume = 12,
    	year = 2008
    }
    
  6. J -H Haunert.
    A Symmetry Detector for Map Generalization and Urban-Space Analysis.
    ISPRS Journal of Photogrammetry and Remote Sensing 74:66–77, 2012. PDF, DOI BibTeX

    @article{Haunert2012,
    	abstract = "This article presents an algorithmic approach to the problem of finding symmetries in building footprints, which is motivated by map generalization tasks such as symmetry-preserving building simplification and symmetry-aware grouping and aggregation. Moreover, symmetries in building footprints may be used for landmark selection and building classification. The presented method builds up on existing methods for symmetry detection in vector data that use algorithms for string matching. It detects both mirror symmetries and repetitions of geometric structures. In addition to the existing vector-based methods, the new method finds partial symmetries in polygons while allowing for small geometric errors and, based on a least-squares approach, computes optimally adjusted mirror axes and assesses their quality. Finally, the problem of grouping symmetry relations is addressed with an algorithm that finds mirror axes that are almost collinear. The presented approach was tested on a large building dataset of the metropolitan Boston area and its results were compared with results that were manually generated in an empirical test. The symmetry relations that the participants of the test considered most important were found by the algorithm. Future work will deal with the integration of information on symmetry relations into algorithms for map generalization.",
    	author = "Haunert, J.-H.",
    	doi = "http://www.sciencedirect.com/science/article/pii/S0924271612001517",
    	journal = "ISPRS Journal of Photogrammetry and Remote Sensing",
    	pages = "66--77",
    	pdf = "http://www1.informatik.uni-wuerzburg.de/pub/haunert/pdf/HaunertISPRS2012.pdf",
    	timestamp = "2013-03-13T10:45:41.000+0100",
    	title = "A Symmetry Detector for Map Generalization and Urban-Space Analysis",
    	volume = 74,
    	year = 2012
    }
    
  7. J -H Haunert and L Sering.
    Drawing Road Networks with Focus Regions.
    IEEE Transactions on Visualization and Computer Graphics (Proc. Information Visualization 2011) 17(12):2555–2562, 2011. PDF BibTeX

    @article{haunertSering2011,
    	abstract = "Mobile users of maps typically need detailed information about their surroundings plus some context information about remote places. In order to avoid that the map partly gets too dense, cartographers have designed mapping functions that enlarge a user-defined focus region  such functions are sometimes called fish-eye projections. The extra map space occupied by the enlarged focus region is compensated by distorting other parts of the map. We argue that, in a map showing a network of roads relevant to the user, distortion should preferably take place in those areas where the network is sparse. Therefore, we do not apply a predefined mapping function. Instead, we consider the road network as a graph whose edges are the road segments. We compute a new spatial mapping with a graph-based optimization approach, minimizing the square sum of distortions at edges. Our optimization method is based on a convex quadratic program (CQP); CQPs can be solved in polynomial time. Important requirements on the output map are expressed as linear inequalities. In particular, we show how to forbid edge crossings. We have implemented our method in a prototype tool. For instances of different sizes, our method generated output maps that were far less distorted than those generated with a predefined fish-eye projection. Future work is needed to automate the selection of roads relevant to the user. Furthermore, we aim at fast heuristics for application in real-time systems.",
    	author = "Haunert, J.-H. and Sering, L.",
    	journal = "IEEE Transactions on Visualization and Computer Graphics (Proc. Information Visualization 2011)",
    	number = 12,
    	pages = "2555--2562",
    	pdf = "http://www1.informatik.uni-wuerzburg.de/pub/haunert/pdf/HaunertSering2011.pdf",
    	timestamp = "2012-04-12T14:42:23.000+0200",
    	title = "Drawing Road Networks with Focus Regions",
    	volume = 17,
    	year = 2011
    }
    
  8. J -H Haunert and A Wolff.
    Area aggregation in map generalisation by mixed-integer programming.
    International Journal of Geographical Information Science 24(12):1871–1897, 2010. URL PDF BibTeX

    @article{haunertwolff2010b,
    	abstract = "Topographic databases normally contain areas of different land cover classes, commonly defining a planar partition, that is, gaps and overlaps are not allowed. When reducing the scale of such a database, some areas become too small for representation and need to be aggregated. This unintentionally but unavoidably results in changes of classes. In this article we present an optimisation method for the aggregation problem. This method aims to minimise changes of classes and to create compact shapes, subject to hard constraints ensuring aggregates of sufficient size for the target scale. To quantify class changes we apply a semantic distance measure. We give a graph theoretical problem formulation and prove that the problem is NP-hard, meaning that we cannot hope to find an efficient algorithm. Instead, we present a solution by mixed-integer programming that can be used to optimally solve small instances with existing optimisation software. In order to process large datasets, we introduce specialised heuristics that allow certain variables to be eliminated in advance and a problem instance to be decomposed into independent sub-instances. We tested our method for a dataset of the official German topographic database ATKIS with input scale 1:50,000 and output scale 1:250,000. For small instances, we compare results of this approach with optimal solutions that were obtained without heuristics. We compare results for large instances with those of an existing iterative algorithm and an alternative optimisation approach by simulated annealing. These tests allow us to conclude that, with the defined heuristics, our optimisation method yields high-quality results for large datasets in modest time.",
    	author = "Haunert, J.-H. and Wolff, A.",
    	journal = "International Journal of Geographical Information Science",
    	number = 12,
    	pages = "1871--1897",
    	pdf = "http://www1.informatik.uni-wuerzburg.de/pub/haunert/pdf/HaunertWolff2010b.pdf",
    	timestamp = "2011-11-07T12:01:05.000+0100",
    	title = "Area aggregation in map generalisation by mixed-integer programming",
    	url = "http://www.informaworld.com/smpp/content~db=all~content=a930246337~tab=content",
    	volume = 24,
    	year = 2010
    }
    
  9. T C Dijk and J -H Haunert.
    Interactive Focus Maps Using Least-Squares Optimization.
    International Journal of Geographical Information Science 28(10):2052–2075, 2014. DOI BibTeX

    @article{VanDijkHaunert,
    	author = "T. C. van Dijk and J.-H. Haunert",
    	doi = "10.1080/13658816.2014.887718",
    	journal = "International Journal of Geographical Information Science",
    	number = 10,
    	pages = "2052--2075",
    	title = "Interactive Focus Maps Using Least-Squares Optimization",
    	volume = 28,
    	year = 2014
    }
    

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