Visually Mediated Interaction Using Learnt Gestures and Camera Control

  • Authors:
  • A. Jonathan Howell;Hilary Buxton

  • Affiliations:
  • -;-

  • Venue:
  • GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
  • Year:
  • 2001

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Abstract

In this paper we introduce connectionist techniques for visually mediated interaction to be used, for example, in video-conferencing applications. First, we briefly present background work on recognition of identity, expression and pose using Radial Basis Function (RBF) networks. Flexible, example-based, learning methods allow a set of specialised networks to be trained. Second, we address the problem of gesture-based communication and attentional focus using Time-Delay versions of the networks. Colour/motion cues are used to direct face detection and the capture of 'attentional frames' surrounding the upper torso and head of the subjects, which focus the processing for visually mediated interaction. Third, we present methods for the gesture recognition and behaviour (user-camera) coordination in the system. In this work, we are taking an appearance-based approach and use the specific phases of communicative gestures to control the camera systems in an integrated system.