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Support Vector Machine Learning for Gesture Signal Estimation with a Piezo Resistive Fabric Touch Surface
Sun, 07/04/2010 - 01:10 — AdrianFreed
| Title | Support Vector Machine Learning for Gesture Signal Estimation with a Piezo Resistive Fabric Touch Surface |
| Publication Type | Conference Paper |
| Year of Publication | 2010 |
| Authors | Schmeder, Andrew, and Freed Adrian |
| Conference Name | NIME |
| Conference Location | Sydney, Australia |
| Abstract | The design of an unusually simple fabric-based touch and pressure sensor is introduced. An analysis of the raw sensor data is shown to have significant non-linearities and non-uniform noise. Using support vector machine learning and a state-dependent adaptive filter it is demonstrated that these problems can be overcome. The method is evaluated quantitatively using a statistical estimate of the instantaneous rate of information transfer. The SVM regression alone is shown to improve the gesture signal information rate by up to 20% with zero added latency, and in combination with filtering by 40% subject to a constant latency bound of 10 milliseconds. |