Toward natural interaction in the real world: real-time gesture recognition

  • Authors:
  • Ying Yin;Randall Davis

  • Affiliations:
  • MIT CSAIL, Cambridge MA;MIT CSAIL, Cambridge MA

  • Venue:
  • International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
  • Year:
  • 2010

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Abstract

Using a new hand tracking technology capable of tracking 3D hand postures in real-time, we developed a recognition system for continuous natural gestures. By natural gestures, we mean those encountered in spontaneous interaction, rather than a set of artificial gestures chosen to simplify recognition. To date we have achieved 95.6% accuracy on isolated gesture recognition, and 73% recognition rate on continuous gesture recognition, with data from 3 users and twelve gesture classes. We connected our gesture recognition system to Google Earth, enabling real time gestural control of a 3D map. We describe the challenges of signal accuracy and signal interpretation presented by working in a real-world environment, and detail how we overcame them.