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De-SIGN: Robust Gesture Recognition in Conceptual Design, Sensor Analysis and Synthesis

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Advances in Robotics and Virtual Reality

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 26))

Abstract

Designing in Virtual Reality systems may bring significant advantages for the preliminary exploration of the design concept in 3D. In this chapter, our purpose is to provide a design platform in VR, integrating data gloves and the sensor jacket that consists of piezo-resistive sensor threads in a sensor network. Unlike the common gesture recognition approaches, that require the assistance of expensive devices such as cameras or Precision Position Tracker (PPT) devices, our sensor network eliminates both the need for additional devices and the limitation of mobility. We developed a Gesture Recognition System (De-SIGN) in various iterations. De-SIGN decodes design gestures. In this chapter, we present the system architecture for De-SIGN, its sensor analysis and synthesis method (SenSe) and the Sparse Representation-based Classification (SRC) algorithm we have developed for gesture signals, and discussed the system’s performance providing the recognition rates. The gesture recognition algorithm presented here is highly accurate regardless of the signal acquisition method used and gives excellent results even for high dimensional signals and large gesture dictionaries. Our findings state that gestures can be recognized with over 99% accuracy rate using the Sparse Representation-based Classification (SRC) algorithm for user-independent gesture dictionaries and 100% for user-dependent.

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Author information

Authors and Affiliations

  1. Virtual and Interactive Simulations of Reality (VISOR), Research Group Department of Computing, Faculty of Science, Macquarie University, Sydney, NSW, 2109, Australia

    Manolya Kavakli & Ali Boyali

Authors
  1. Manolya Kavakli
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  2. Ali Boyali
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Editor information

Editors and Affiliations

  1. Department of Computer Science, COMSATS Institute of Information Technology, M.A. Jinnah Campus Defence Road, Lahore, Pakistan

    Tauseef Gulrez

  2. Faculty of Computer and Information Information Technology Department, Cairo University, 5 Ahmed Zewal St., Giza, Orman, Egypt

    Aboul Ella Hassanien

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Kavakli, M., Boyali, A. (2012). De-SIGN: Robust Gesture Recognition in Conceptual Design, Sensor Analysis and Synthesis. In: Gulrez, T., Hassanien, A.E. (eds) Advances in Robotics and Virtual Reality. Intelligent Systems Reference Library, vol 26. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23363-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-23363-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23362-3

  • Online ISBN: 978-3-642-23363-0

  • eBook Packages: EngineeringEngineering (R0)

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