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Sign Segmentation Using Dynamics and Hand Configuration for Semi-automatic Annotation of Sign Language Corpora

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Gesture and Sign Language in Human-Computer Interaction and Embodied Communication (GW 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7206))

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Abstract

This paper address the problem of sign language video annotation. Nowadays sign language segmentation is manually performed. This is time consuming, error prone and no reproducible. In this paper we intend to provide an automatic approach to segment signs. We use a particle filter based approach to track hands and head. Motion features are used to classify segments performed with one or two hands and to detect events. Events that have been detected in the middle of a sign are removed considering hand shape features. Hand shape is characterized using similarity measurements. Evaluation has been performed and has shown the performance and limitation of the proposed approach.

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Author information

Authors and Affiliations

  1. IRIT (UPS - CNRS UMR 5505), Université Paul Sabatier, 118 Route de Narbonne, F-31062, Toulouse Cedex 9, France

    Matilde Gonzalez & Christophe Collet

Authors
  1. Matilde Gonzalez
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  2. Christophe Collet
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Editor information

Editors and Affiliations

  1. “Athena” RC - Research and Innovation Center in Information, Communication and Knowledge Technologies, Institute for Language and Speech Processing (ILSP), Artemidos 6 & Epidavrou, Maroussi,, 15125, Athens, Greece

    Eleni Efthimiou

  2. Dep. of Informatics and Telecommunications, Speech and Accessibility Lab., National and Kapodistrian University of Athens, 15784, Athens, Greece

    Georgios Kouroupetroglou

  3. “Athena” RC - Research and Innovation Center in Information, Communication and Knowledge Technologies, Processing (ILSP), Artemidos 6 & Epidavrou, Maroussi, 15125, Athens, Greece

    Stavroula-Evita Fotinea

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© 2012 Springer-Verlag Berlin Heidelberg

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Gonzalez, M., Collet, C. (2012). Sign Segmentation Using Dynamics and Hand Configuration for Semi-automatic Annotation of Sign Language Corpora. In: Efthimiou, E., Kouroupetroglou, G., Fotinea, SE. (eds) Gesture and Sign Language in Human-Computer Interaction and Embodied Communication. GW 2011. Lecture Notes in Computer Science(), vol 7206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34182-3_19

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  • DOI: https://doi.org/10.1007/978-3-642-34182-3_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34181-6

  • Online ISBN: 978-3-642-34182-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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