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Multiple Hypothesis Tracking with Sign Language Hand Motion Constraints

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Computer Analysis of Images and Patterns (CAIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9257))

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Abstract

In this paper, we propose to incorporate prior knowledge from sign language linguistic models about the motion of the hands within a multiple hypothesis tracking framework. A critical component for automated visual sign language recognition is the tracking of the signer’s hands, especially when faced with frequent and persistent occlusions and complex hand interactions. Hand motion constraints identified by sign language phonological models, such as the hand symmetry condition, are used as part of the data association process. Initial experimental results show the validity of the proposed approach.

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Author information

Authors and Affiliations

  1. Systems and Control Engineering, Faculty of Engineering, University of Malta, Msida, Malta

    Mark Borg & Kenneth P. Camilleri

Authors
  1. Mark Borg
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  2. Kenneth P. Camilleri
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Corresponding author

Correspondence to Mark Borg .

Editor information

Editors and Affiliations

  1. University of Malta, Msida, Malta

    George Azzopardi

  2. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

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Borg, M., Camilleri, K.P. (2015). Multiple Hypothesis Tracking with Sign Language Hand Motion Constraints. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9257. Springer, Cham. https://doi.org/10.1007/978-3-319-23117-4_18

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  • DOI: https://doi.org/10.1007/978-3-319-23117-4_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23116-7

  • Online ISBN: 978-3-319-23117-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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