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Two-stage Recognition of Raw Acceleration Signals for 3-D Gesture-Understanding Cell Phones

Abstract : As many functionalities like cameras and MP3 players are converged to cell phones, more intuitive interaction methods are essential beyond tiny keypads. In this paper, we present gesture-based interactions and their two-stage recognition algorithm. Acceleration signals are generated from accelerometer. At the first stage, they are hierarchically modelled and matched as basic component and their relationships by Bayesian networks. At the second stage, they are further classified by SVMs for resolving confusing pairs. Our system showed enough recognition performance for commercialization; with 100 novice users, the average recognition rate was 96.9% on 11 gestures (digits 1-9, O, X). The algorithms have been adopted in the world-first gesture-recognizing Samsung cell phones since 2005.
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Contributor : Anne Jaigu Connect in order to contact the contributor
Submitted on : Thursday, October 5, 2006 - 1:30:20 PM
Last modification on : Friday, October 23, 2020 - 4:38:37 PM
Long-term archiving on: : Tuesday, April 6, 2010 - 6:27:25 PM


  • HAL Id : inria-00103854, version 1



Sung-Jung Cho, Eunseok Choi, Won-Chul Bang, Jing Yang, Junil Sohn, et al.. Two-stage Recognition of Raw Acceleration Signals for 3-D Gesture-Understanding Cell Phones. Tenth International Workshop on Frontiers in Handwriting Recognition, Université de Rennes 1, Oct 2006, La Baule (France). ⟨inria-00103854⟩



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