Gesture Recognition with a 3-D Accelerometer

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Gesture Recognition with a 3-D Accelerometer
Abstract. Gesture-based interaction, as a natural way for human-computer interaction, has a wide range of applications in ubiquitous computing environment. This paper presents an acceleration-based gesture recognition approach, called FDSVM (Frame-based Descriptor and multi-class SVM), which needs only a wearable 3-dimensional accelerometer. With FDSVM, firstly, the acceleration data of a gesture is collected and represented by a frame-based descriptor, to extract the discriminative information. Then a SVM-based multi-class gesture classifier is built for recognition in the nonlinear gesture feature space. Extensive experimental results on a data set with 3360 gesture samples of 12 gestures over weeks demonstrate that the proposed FDSVM approach significantly outperforms other four methods: DTW, Naïve Bayes, C4.5 and HMM. In the user-dependent case, FDSVM achieves the recognition rate of 99.38% for the 4 direction gestures and 95.21% for all the 12 gestures. In the user-independent ca...
Jiahui Wu, Gang Pan, Daqing Zhang, Guande Qi, Shij
Added 27 Jul 2010
Updated 27 Jul 2010
Type Conference
Year 2009
Where UIC
Authors Jiahui Wu, Gang Pan, Daqing Zhang, Guande Qi, Shijian Li
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