toolkit.xml
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<?xml version="1.0" encoding="UTF-8" ?>
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<opendatametainfo>
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<title>ReSEED: Social Event dEtection Dataset</title> |
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<organisation>
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<name>ReSEED: Social Event dEtection Dataset</name> |
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<url>https://cit-ec.de</url> |
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</organisation>
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<description>
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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. |
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</description>
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<!--
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<projects>
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<project>
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<name>MINDA</name>
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<url>http://www.cit-ec.de/research/MINDA"</url>
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<description>
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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.
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</description>
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</project>
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<project>
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<name>CORTESMA</name>
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<url>http://www.cit-ec.de/research/CORTESMA"</url>
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<description>
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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.
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</description>
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</project>
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</projects>
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-->
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<version>v1.0.0</version> |
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<date>2014-03-14</date> |
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<creators>
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<creator>
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<name>Timo Reuter</name> |
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<url>http://www.cit-ec.de/users/treuter</url> |
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</creator>
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</creators>
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<!--
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<contributors>
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<contributor>
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<name>-</name>
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<url>-</url>
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</contributor>
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</contributors>
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-->
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<downloadurls>
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_readme.pdf</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures.tar.gz</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_train.tar.gz</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_test.tar.gz</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_events.tar.gz</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_train_1.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_train_2.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_train_3.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_train_4.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_train_5.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_train_6.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_train_7.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_test_1.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_test_2.tar.bz2</downloadurl> |
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<downloadurl>http://greententacle.techfak.uni-bielefeld.de/reseed/reseed_pictures_jpgs_test_3.tar.bz2</downloadurl> |
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</downloadurls>
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<license>
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Open Data Commons Attribution License (ODBC-By) v1.0: http://opendatacommons.org/licenses/by/1.0/ |
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</license>
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<keywords>
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<keyword>Clustering</keyword> |
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<keyword>Event Detection</keyword> |
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<keyword>Machine Learning</keyword> |
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</keywords>
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<!--
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<structure>
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Time series of joint angles and hand positions. Note that the Cyberglove captures at approximately 90hz and the Vicon system at exactly 200hz.
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</structure>
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-->
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<formats>
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<format>XML</format> |
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</formats>
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<!--
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<relation>http://pub.uni-bielefeld.de/pub?func=drec&id=2034003"</relation>
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-->
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<acknowledgements>
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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. |
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</acknowledgements>
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</opendatametainfo>
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<!-- Future: Add RDF description/attributes -->
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