Hidden Markov Model Based Continuous Online Gesture Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Novel, minimalist haptic gesture interaction for mobile devices
Proceedings of the third Nordic conference on Human-computer interaction
Enabling fast and effortless customisation in accelerometer based gesture interaction
Proceedings of the 3rd international conference on Mobile and ubiquitous multimedia
Gesture recognition with a Wii controller
Proceedings of the 2nd international conference on Tangible and embedded interaction
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Feature fusion for 3D hand gesture recognition by learning a shared hidden space
Pattern Recognition Letters
Locally regularized sliced inverse regression based 3D hand gesture recognition on a dance robot
Information Sciences: an International Journal
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With the release of the Nintendo Wii in 2006, the use of haptic force gestures has become a very popular form of input for interactive entertainment. However, current gesture recognition techniques utilised in Nintendo Wii games fall prey to a lack of control when it comes to recognising simple gestures. This paper presents a simple gesture recognition technique called Peak Testing which gives greater control over gesture interaction. This recognition technique locates force peaks in continuous force data (provided by a gesture device such as the Wiimote) and then cancels any peaks which are not meant for input. Peak Testing is therefore technically able to identify movements in any direction. This paper applies this recognition technique to control virtual instruments and investigates how users respond to this interaction. The technique is then explored as the basis for a robust way to navigate menus with a simple flick of the wrist. We propose that this flick-form of interaction could be a very intuitive way to navigate Nintendo Wii menus instead of the current pointer techniques implemented.