Title :
3D finger posture detection and gesture recognition on touch surfaces
Abstract :
As the use of touch surfaces for user interfaces becomes more common, advances in the interpretations of touch input have lagged behind and are still limited to only the most basic of motions. Richer gesture-based human-computer interactions could serve to advance a wider acceptance of touch-based technology in a variety of fields. Using a 3D finger posture rather than just the 2D contact point in gesture definition opens the door to very rich, expressive, and intuitive gesture metaphors. In this paper, we present algorithms and methods for estimating the parameters of 3D finger postures on a touch surface, as well as a gesture recognition framework which uses an Artificial Neural Network to recognize 3D gestures on touchpads and touchscreens.
Keywords :
gesture recognition; human computer interaction; neural nets; touch sensitive screens; 2D contact point; 3D finger posture detection; 3D gestures; artificial neural network; gesture metaphors; gesture recognition; gesture-based human-computer interactions; touch surfaces; touchpads; touchscreens; Artificial neural networks; Equations; Gesture recognition; Image edge detection; Mathematical model; Principal component analysis; Vectors;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1871-6
Electronic_ISBN :
978-1-4673-1870-9
DOI :
10.1109/ICARCV.2012.6485185