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Emblematic Gestures Recognition

[+] Author Affiliations
Ryad Chellali

Italian Institute of Technology, Genova, Italy

Ilaria Renna

Université P&M Curie Paris, Paris, FranceItalian Institute of Technology, Genova, Italy

Paper No. ESDA2012-82481, pp. 755-761; 7 pages
doi:10.1115/ESDA2012-82481
From:
  • ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis
  • Volume 2: Applied Fluid Mechanics; Electromechanical Systems and Mechatronics; Advanced Energy Systems; Thermal Engineering; Human Factors and Cognitive Engineering
  • Nantes, France, July 2–4, 2012
  • Conference Sponsors: International
  • ISBN: 978-0-7918-4485-4
  • Copyright © 2012 by ASME

abstract

This paper presents a framework allowing emblematic gestures detection, segmentation and their recognition for human-robots interaction purposes. This framework is based on a new coding of arms’ kinematics reflecting both the muscular activity of the performer and the appearance of arm seen by the recipient when a gesture is performed. Following that, gestures can be seen as sequences of torques activations leading arm’s parts to express a comprehensive meaning. In addition, these sequences have very stable topologies and shapes regardless to performers. This facilitates the generalization of the recognition process with a minimalistic learning effort for online usages. Promising results were obtained for a set of 5 classes of gestures performed by 19 different persons.

Copyright © 2012 by ASME

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