ReSEED (Social Event dEtection Dataset)

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<opendatametainfo>

  <title>ReSEED: Social Event dEtection Dataset</title>

  <organisation>

        <name>ReSEED: Social Event dEtection Dataset</name>

        <url>https://cit-ec.de</url>

  </organisation>

  <description>

Dataset from Flickr for event detection. Contains 437,370 pictures annotated with metadata in a csv file. Released under a CC license that allows a modification.

</description>

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  <projects>

        <project>

        <name>MINDA</name>

        <url>http://www.cit-ec.de/research/MINDA"</url>

        <description>

MINDA is creating incrementally growing database of manual interactions to help put manual intelligence research on a firmer empirical bases. This involves the study of manual interactions in humans using a multi-sensing approach. The database contains: geometry information, tactile sensor information, vision information and sound information. Using these multimodal information sources allows us to build models that can aid robots to carry out complex tasks of the type that humans perform with ease.

        </description>

        </project>

        <project>

        <name>CORTESMA</name>

        <url>http://www.cit-ec.de/research/CORTESMA"</url>

        <description>

                CORTESMA investigated hand kinematics and mental representations of grasping movements directed towards real and virtual spherical objects systematically varying                         in size. Results suggest that grasping movements are influenced by object size at an early stage of the movement for real and virtual objects. The analyses of mental                         representations (via SDA) and of motor synergies (via PCA) reveal a separation of the smallest three objects from the larger ones, pointing towards a conceptual                         influence on the grasping movement.

        </description>

        </project>        

  </projects>

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  <version>v1.0.0</version>

  <date>2014-03-14</date>

  <creators>

        <creator>

          <name>Timo Reuter</name>

        <url>http://www.cit-ec.de/users/treuter</url>

        </creator>

  </creators>

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  <license>

        MINDA, CORTESMA: 'Kinematic data of grasping movements directed towards virtual and real objects' Copyright(c) Jonathan Maycock, Bettina Blaesing, Till Bockemuehl,Helge                 Ritter and Thomas Schack http://opendata.cit-ec.de/projects/virtual-and-real-grasping http://opendata.cit-ec.de/projects/virtual-and-real-grasping. There is NO warranty; not                 even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. The development of this database was supported by the Excellence Cluster EXC 277 Cognitive Interaction                 Technology. The Excellence Cluster EXC 277 is a grant of the Deutsche Forschungsgemeinschaft (DFG) in the context of the German Excellence Initiative. 'Kinematic data of                 grasping movements directed towards virtual and real objects' is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in                 individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/

  </license>

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  <keywords>

                <keyword>Question Answering</keyword>

                <keyword>Linked Data</keyword>

                <keyword>Natural Language Processing</keyword>

                <keyword>Semantic Web</keyword>

  </keywords>

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  <structure>

        Time series of joint angles and hand positions. Note that the Cyberglove captures at approximately 90hz and the Vicon system at exactly 200hz. 

  </structure>

  -->

  <formats>

          <format>XML</format>

  </formats>

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  <relation>http://pub.uni-bielefeld.de/pub?func=drec&#38;id=2034003"</relation>

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  <acknowledgements>

        The development of this database was supported by the Excellence Cluster EXC 277 Cognitive Interaction Technology. The Excellence Cluster EXC 277 is a grant of the Deutsche                 Forschungsgemeinschaft (DFG) in the context of the German Excellence Initiative. 

  </acknowledgements>

</opendatametainfo>

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