A gesture-based method for natural interaction in smart spaces

Wang, Xian and Bernardos Barbolla, Ana M. and Besada Portas, Juan Alberto and Metola Moreno, Eduardo and Casar Corredera, Jose Ramon (2015). A gesture-based method for natural interaction in smart spaces. "Journal of Ambient Intelligence and Smart Environments (JAISE)", v. 7 (n. 4); pp. 535-562. ISSN 1876-1364. https://doi.org/10.3233/AIS-150325.


Title: A gesture-based method for natural interaction in smart spaces
  • Wang, Xian
  • Bernardos Barbolla, Ana M.
  • Besada Portas, Juan Alberto
  • Metola Moreno, Eduardo
  • Casar Corredera, Jose Ramon
Item Type: Article
Título de Revista/Publicación: Journal of Ambient Intelligence and Smart Environments (JAISE)
Date: 2015
ISSN: 1876-1364
Volume: 7
Freetext Keywords: Natural interaction, mobile applications, smart objects, smart spaces, pattern recognition, gesture recognition
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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A key issue when making spaces smart is the availability of satisfying and personalized interaction methods, for the user to comfortably manage the physical and virtual resources in the environment. Among the multiple interaction approaches that are nowadays being explored with this objective, gesture-based ones seem to have a great potential. In this line, this research describes a gesture-based interaction method that uses a specific grammar to control and network objects in a smart space. The method’s grammar establishes that the user has to identify the object to interact with by performing an individuation gesture primitive (the object’s initial letter), then using an action gesture primitive to indicate the action to perform. The action may involve a second object, which will be identified as the first one. The user will be able to personalize the action gestures in the vocabulary, and to configure the commands assigned to gestures, and the system will provide interaction cues for the user not to feel lost. The main component of the system is a gesture recognition module based on an adapted Dynamic Time Warping algorithm. This module works sharply on acceleration or position data inputs, being suitable to deploy device instrumented or infrastructure-based solutions for gesture recognition (i.e. smartphone or Kinect-based ones). The average recognition rate is 93.63% for smartphone-based recognition and 98.64% for Kinect-based one, respectively. The paper also details the architecture and software tools that enables the interaction method to work in a real environment.

Funding Projects

Madrid Regional GovernmentS2009/TIC-1485CONTEXTSUnspecifiedConceptos y tecnologías para el desarrollo de servicio

More information

Item ID: 42000
DC Identifier: http://oa.upm.es/42000/
OAI Identifier: oai:oa.upm.es:42000
DOI: 10.3233/AIS-150325
Official URL: http://content.iospress.com/articles/journal-of-ambient-intelligence-and-smart-environments/ais325
Deposited by: Memoria Investigacion
Deposited on: 27 Jul 2016 18:38
Last Modified: 27 Jul 2016 18:38
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