untitled
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<identifier>oai:HAL:hal-00802340v1</identifier>
<datestamp>2015-02-06</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>The ILGDB database of realistic pen-based gestural commands</title>
<creator>Renau-Ferrer, Ney</creator>
<creator>Li, Peiyu</creator>
<creator>Delaye, Adrien</creator>
<creator>Anquetil, Eric</creator>
<contributor>INTUIDOC ; Laboratoire de Mathématiques Informatique et Applications (LAMIA) ; Université des Antilles et de la Guyane (UAG) - Université des Antilles et de la Guyane (UAG) - INTUIDOC (IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - CNRS - Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - CNRS</contributor>
<contributor>INTUIDOC (IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA) - Institut National des Sciences Appliquées (INSA) - CNRS</contributor>
<description>International audience</description>
<source>ICPR2012 - 21st International Conference on Pattern Recognition</source>
<coverage>Tsukuba, Japan</coverage>
<identifier>hal-00802340</identifier>
<identifier>https://hal.inria.fr/hal-00802340</identifier>
<identifier>https://hal.inria.fr/hal-00802340/document</identifier>
<source>https://hal.inria.fr/hal-00802340</source>
<source>ICPR2012 - 21st International Conference on Pattern Recognition, 2012, Tsukuba, Japan. pp.3741-3744</source>
<language>en</language>
<subject>[INFO.INFO-HC] Computer Science/Human-Computer Interaction</subject>
<type>Conference papers</type>
<description lang=en>In this paper, we introduce the Intuidoc-Loustic Gestures DataBase (ILGDB), a new publicly available database of realistic pen-based gestures for evaluation of recognition systems in pen-enabled interfaces. ILGDB was collected in a real world context and in an immersive environment. As it contains a large number of unconstrained user-defined gestures, ILGDB offers a unique diversity of content that is likely to serve as a precious tool for benchmarking of gesture recognition systems. We report first baseline experimental results on the task of Writer-Dependent gesture recognition.</description>
<date>2012</date>
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