Adaptive motion-based gesture recognition interface for mobile phones

Authors:
Jari Hannuksela;Mark Barnard;Pekka Sangi;Janne Heikkilä
Affiliations:
Machine Vision Group, Infotech Oulu, Department of Electrical and Information Engineering, University of Oulu, Finland;Machine Vision Group, Infotech Oulu, Department of Electrical and Information Engineering, University of Oulu, Finland;Machine Vision Group, Infotech Oulu, Department of Electrical and Information Engineering, University of Oulu, Finland;Machine Vision Group, Infotech Oulu, Department of Electrical and Information Engineering, University of Oulu, Finland
Venue:
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Year:
2008

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Abstract

In this paper, we introduce a new vision based interaction technique for mobile phones. The user operates the interface by simply moving a finger in front of a camera. During these movements the finger is tracked using a method that embeds the Kalman filter and ExpectationMaximization (EM) algorithms. Finger movements are interpreted as gestures using Hidden Markov Models (HMMs). This involves first creating a generic model of the gesture and then utilizing unsupervised Maximum a Posteriori (MAP) adaptation to improve the recognition rate for a specific user. Experiments conducted on a recognition task involving simple control commands clearly demonstrate the performance of our approach.