@inproceedings {INPROC-2010-66,
    author = {Bernhard Schmitz},
    title = {{The ViibraCane - A White Cane for Tactile Navigation Guidance}},
    booktitle = {Proceedings of the California State University, Northridge Center on Disabilities' 25th Annual International Technology and Persons with Disabilities Conference (CSUN 2010)},
    address = {San Diego},
    publisher = {Online},
    institution = {Universit{\"a}t Stuttgart : Sonderforschungsbereich SFB 627 (Nexus: Umgebungsmodelle f{\"u}r mobile kontextbezogene Systeme), Germany},
    type = {Konferenz-Beitrag},
    month = {M{\"a}rz},
    year = {2010},
    language = {Deutsch},
    cr-category = {K.4.2 Computers and Society Social Issues},
    ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2010-66/INPROC-2010-66.pdf},
    department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Visualisierung und Interaktive Systeme, Visualisierung und Interaktive Systeme},
    abstract = {The ViibraCane, an extension to the navigation system TANIA, is a white cane
      that can be used as a tactile guiding device for navigation tasks.},
    url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2010-66&engl=0}
 }

@inproceedings {INPROC-2010-64,
    author = {Bernhard Schmitz and Thomas Ertl},
    title = {{Making Digital Maps Accessible Using Vibrations}},
    booktitle = {Computers Helping People with Special Needs. 12th International Conference, ICCHP 2010, Proceedings},
    address = {Heidelberg},
    publisher = {Springer Berlin Heidelberg},
    institution = {Universit{\"a}t Stuttgart : Sonderforschungsbereich SFB 627 (Nexus: Umgebungsmodelle f{\"u}r mobile kontextbezogene Systeme), Germany},
    series = {Lecture Notes in Computer Science},
    volume = {6179},
    pages = {100--107},
    type = {Konferenz-Beitrag},
    month = {Juli},
    year = {2010},
    doi = {10.1007/978-3-642-14097-6_18},
    isbn = {978-3-642-14096-9},
    keywords = {Haptic Maps; Vibrating Maps; Blind Users},
    language = {Englisch},
    cr-category = {K.4.2 Computers and Society Social Issues},
    ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2010-64/INPROC-2010-64.pdf},
    department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Visualisierung und Interaktive Systeme, Visualisierung und Interaktive Systeme},
    abstract = {In order to allow blind and deafblind people to use and explore electronically
      available maps, we have developed a system that displays maps in a tactile way
      using a standard rumble gamepad. The system is intended for both on-site and
      off-site use and therefore includes mechanisms for getting overviews of larger
      regions as well as for the exploration of small areas.},
    url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2010-64&engl=0}
 }

@inproceedings {INPROC-2010-40,
    author = {Julia Moehrmann and Xin Wang and Gunther Heidemann},
    title = {{Motion based situation recognition in group meetings}},
    booktitle = {Proceedings of SPIE Conference on Image Processing: Machine Vision Applications III},
    editor = {David Fofi and Kurt S. Niel},
    address = {San Jose, California, USA},
    publisher = {SPIE},
    institution = {Universit{\"a}t Stuttgart : Sonderforschungsbereich SFB 627 (Nexus: Umgebungsmodelle f{\"u}r mobile kontextbezogene Systeme), Germany},
    series = {Proceedings of SPIE},
    volume = {7538},
    pages = {75380--75380},
    type = {Konferenz-Beitrag},
    month = {Januar},
    year = {2010},
    doi = {http://dx.doi.org/10.1117/12.838963},
    keywords = {Group meeting recognition; situation recognition; Hidden Markov Model; Motion features},
    language = {Englisch},
    cr-category = {I.5.4 Pattern Recognition Applications,
                   I.4.6 Image Processing and Computer Vision Segmentation,
                   I.4.9 Image Processing and Computer Vision Applications},
    ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2010-40/INPROC-2010-40.pdf},
    contact = {julia.moehrmann@vis.uni-stuttgart.de},
    department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Visualisierung und Interaktive Systeme, Visualisierung und Interaktive Systeme},
    abstract = {We present an unobtrusive vision based system for the recognition of situations
      in group meetings. The system uses a three-stage architecture, consisting of
      one video processing stage and two classification stages. The video processing
      stage detects motion in the videos and extracts up to 12 features from this
      data. The classification stage uses Hidden Markov Models to first identify the
      activity of every participant in the meeting and afterwards recognize the
      situation as a whole. The feature extraction uses position information of both
      hands and the face to extract motion features like speed, acceleration and
      motion frequency, as well as distance based features. We investigate the
      discriminative ability of these features and their applicability to the task of
      interaction recognition. A two-stage Hidden Markov Model classifier is applied
      to perform the recognition task. The developed system classifies the situation
      in 94\% of all frames in our video test set correctly, where 3\% of the test data
      is misclassified due to contradictory behavior of the participants. The results
      show that unimodal data can be sufficient to recognize complex situations.},
    url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2010-40&engl=0}
 }

@inproceedings {INPROC-2010-39,
    author = {Julia Moehrmann and Gunther Heidemann},
    title = {{Automatic trajectory clustering for generating ground truth data sets}},
    booktitle = {Proceedings of SPIE Conference on Image Processing: Machine Vision Applications III},
    editor = {David Fofi and Kurt S. Niel},
    address = {San Jose, California, USA},
    publisher = {SPIE},
    institution = {Universit{\"a}t Stuttgart : Sonderforschungsbereich SFB 627 (Nexus: Umgebungsmodelle f{\"u}r mobile kontextbezogene Systeme), Germany},
    series = {Proceedings of SPIE},
    volume = {7538},
    pages = {753808--753808},
    type = {Konferenz-Beitrag},
    month = {Januar},
    year = {2010},
    doi = {http://dx.doi.org/10.1117/12.838954},
    keywords = {Hidden Markov Model; HMM based representation; clustering; ground truth data},
    language = {Deutsch},
    cr-category = {I.2.10 Vision and Scene Understanding,
                   I.4.8 Image Processing and Computer Vision Scene Analysis,
                   I.5.3 Pattern Recognition Clustering,
                   I.5.4 Pattern Recognition Applications},
    ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2010-39/INPROC-2010-39.pdf},
    contact = {julia.moehrmann@vis.uni-stuttgart.de},
    department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Visualisierung und Interaktive Systeme, Visualisierung und Interaktive Systeme},
    abstract = {We present a novel approach towards the creation of vision based recognition
      tasks. A lot of domain specific recognition systems have been presented in the
      past which make use of the large amounts of available video data. The creation
      of ground truth data sets for the training of theses systems remains difficult
      and tiresome. We present a system which automatically creates clusters of 2D
      trajectories. The results of this clustering can then be used to perform the
      actual labeling of the data, or rather the selection of events or features of
      interest by the user. The selected clusters can be used as positive training
      data for a user defined recognition task {\^a}€“ without the need to adapt the
      system. The proposed technique reduces the necessary user interaction and
      allows the creation of application independent ground truth data sets with
      minimal effort. In order to achieve the automatic clustering we have developed
      a distance metric based on the Hidden Markov Model representations of three
      sequences {\^a}€“ movement, speed and orientation {\^a}€“ derived from the initial
      trajectory. The proposed system yields promising results and could prove to be
      an important steps towards mining very large data sets.},
    url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2010-39&engl=0}
 }

@inproceedings {INPROC-2010-35,
    author = {Julia M{\"o}hrmann and Gunter Heidemann and Oliver Siemoneit and Christoph Hubig and Uwe-Philipp K{\"a}ppeler and Paul Levi},
    title = {{Context Generation with Image Based Sensors: An Interdisciplinary Enquiry on Technical and Social Issues and their Implications for System Design}},
    booktitle = {Proceedings of World Academy of Science, Engineering and Technology},
    address = {Capetown},
    publisher = {WASET},
    institution = {Universit{\"a}t Stuttgart : Sonderforschungsbereich SFB 627 (Nexus: Umgebungsmodelle f{\"u}r mobile kontextbezogene Systeme), Germany},
    pages = {262--268},
    type = {Konferenz-Beitrag},
    month = {Januar},
    year = {2010},
    keywords = {Context-aware computing; ethical and social issues; image recognition; requirements in system design},
    language = {Englisch},
    cr-category = {I.4.1 Digitization and Image Capture,
                   I.4.8 Image Processing and Computer Vision Scene Analysis},
    department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Philosophie, Abteilung f{\"u}r Wissenschaftstheorie und Technikphilosophie (IP/WTTP);
                  Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Bildverstehen;
                  Universit{\"a}t Stuttgart, Institut f{\"u}r Visualisierung und Interaktive Systeme, Visualisierung und Interaktive Systeme},
    abstract = {Image data holds a large amount of different context information. However, as
      of today, these resources remain largely untouched. It is thus the aim of this
      paper to present a basic technical framework which allows for a quick and easy
      exploitation of context information from image data especially by non-expert
      users. Furthermore, the proposed framework is discussed in detail concerning
      important social and ethical issues which demand special requirements in system
      design. Finally, a first sensor prototype is presented which meets the
      identified requirements. Additionally, necessary implications for the software
      and hardware design of the system are discussed, rendering a sensor system
      which could be regarded as a good, acceptable and justifiable technical and
      thereby enabling the extraction of context information from image data.},
    url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2010-35&engl=0}
 }

@inproceedings {INPROC-2010-19,
    author = {Carlos L{\"u}bbe and Andreas Brodt and Nazario Cipriani and Harald Sanftmann},
    title = {{NexusVIS: A Distributed Visualization Toolkit for Mobile Applications (Demonstration)}},
    booktitle = {Proceedings of the 8th Annual IEEE International Conference on Pervasive Computing and Communications (PerCom '10); Mannheim, Germany, March 2010},
    publisher = {IEEE Computer Society},
    institution = {Universit{\"a}t Stuttgart : Sonderforschungsbereich SFB 627 (Nexus: Umgebungsmodelle f{\"u}r mobile kontextbezogene Systeme), Germany},
    pages = {1--3},
    type = {Konferenz-Beitrag},
    month = {M{\"a}rz},
    year = {2010},
    isbn = {978-1-4244-5328-3},
    keywords = {Visualisierung, Datenstromverarbeitung},
    language = {Englisch},
    cr-category = {H.2.4 Database Management Systems},
    contact = {carlos.luebbe@ipvs.uni-stuttgart.de},
    department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
                  Universit{\"a}t Stuttgart, Institut f{\"u}r Visualisierung und Interaktive Systeme, Visualisierung und Interaktive Systeme},
    abstract = {Many mobile pervasive applications need to visualize information about the
      user's geographic surroundings combined with data from sensors, which determine
      the user's context. We demonstrate NexusVIS, a distributed visualization
      toolkit for mobile applications. By building upon an existing data stream
      processing system we enable applications to define distributed visualization
      processes as continuous queries. This allows applications to define
      visualization semantics descriptively. Moreover, NexusVIS is capable of
      adapting the visual query at runtime, and thus allows to navigate in the
      visualized scene both automatically and manually through user control.},
    url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2010-19&engl=0}
 }