Summary:
Mäntyjärvi et al. apply discrete HMMs to accelerometer data for gesture recognition. The authors had a previous study that indicated users prefer defining their own gestures, or they prefer intuitive gestures.
The authors add noise into the gestures to increase the recognition of user-defined gestures under certain conditions. This supposedly speeds up the training process since less gestures need to be "drawn". Adding Gaussian noise versus uniform noise might improve the recognition. But not really.
Discussion:
This paper changed courses in the middle and moved from customization to noise addition. The gesture set they tested on was super easy and can be done with Rubine's recognizer. I'd like to see some data that users created and the differences between the user-defined gesture and the DVD gestures.
Subscribe to:
Post Comments (Atom)
1 comment:
Hey, new to the world of haptics and discovered your blog. I am really excited by this technology, do you have any idea of the companies that are developing it?
There are so many applications, is there any consensus on when we will start to see this technology become the standard for a variety of devices? Which sector, gaming, medical, simulators, communications?
Post a Comment