A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Protractor: a fast and accurate gesture recognizer
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Protractor3D: a closed-form solution to rotation-invariant 3D gestures
Proceedings of the 16th international conference on Intelligent user interfaces
User-defined motion gestures for mobile interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
DoubleFlip: a motion gesture delimiter for mobile interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Breaking the status quo: Improving 3D gesture recognition with spatially convenient input devices
VR '10 Proceedings of the 2010 IEEE Virtual Reality Conference
Searching and mining trillions of time series subsequences under dynamic time warping
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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Motivated by the addition of gyroscopes to a large number of new smart phones, we study the effects of combining accelerometer and gyroscope data on the recognition rate of motion gesture recognizers with dimensionality constraints. Using a large data set of motion gestures we analyze results for the following algorithms: Protractor3D, Dynamic Time Warping (DTW) and Regularized Logistic Regression (LR). We chose to study these algorithms because they are relatively easy to implement, thus well suited for rapid prototyping or early deployment during prototyping stages. For use in our analysis, we contribute a method to extend Protractor3D to work with the 6D data obtained by combining accelerometer and gyroscope data. Our results show that combining accelerometer and gyroscope data is beneficial also for algorithms with dimensionality constraints and improves the gesture recognition rate on our data set by up to 4%.