By Topic

Input action classification in a 3D gesture interface for mobile devices

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ogawa, K. ; Fac. of Sci., Japan Women''s Univ., Tokyo, Japan ; Sakata, N. ; Muraiso, T. ; Komuro, T.

In this research we propose a new motion classification method to improve operability of a 3D gesture interface that assists text input on mobile devices. A certain range of time-series finger scale data is cropped and is classified using linear discriminant analysis. To confirm possibility of linear separation, data were visualized using principle component analysis. Experimental result with changing cropping ranges and sampling rates showed that the recognition rate improved when the cropped time is longer, and more than 97.9% recognition rates were achieved with cropping time of 0.77s/0.38s from both/one sides of the peak.

Published in:

Consumer Electronics (GCCE), 2012 IEEE 1st Global Conference on

Date of Conference:

2-5 Oct. 2012