Opportunistic synergy: a classifier fusion engine for micro-gesture recognition

  • Authors:
  • Leonardo Angelini;Francesco Carrino;Stefano Carrino;Maurizio Caon;Denis Lalanne;Omar Abou Khaled;Elena Mugellini

  • Affiliations:
  • University of Applied Sciences Western Switzerland, Fribourg and University of Fribourg, Switzerland;University of Applied Sciences Western Switzerland, Fribourg and University of Fribourg, Switzerland;University of Applied Sciences Western Switzerland, Fribourg and University of Fribourg, Switzerland;University of Applied Sciences Western Switzerland, Fribourg;University of Fribourg, Switzerland;University of Applied Sciences Western Switzerland, Fribourg;University of Applied Sciences Western Switzerland, Fribourg

  • Venue:
  • Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we present a novel opportunistic paradigm for in-vehicle gesture recognition. This paradigm allows using two or more subsystems in a synergistic manner: they can work in parallel but the lack of some of them does not compromise the functioning of the whole system. In order to segment and recognize micro-gestures performed by the user on the steering wheel, we combine a wearable approach based on the electromyography of the user's forearm muscles, with an environmental approach based on pressure sensors integrated directly on the steering wheel. We present and analyze several fusion methods and gesture segmentation strategies. A prototype has been developed and evaluated with data from nine subjects. The results prove that the proposed opportunistic system performs equal or better than each stand-alone subsystem while increasing the interaction possibilities.