This paper describes the implementation of an artificial neural network based adaptive hand positioning and gesture recognition system for multimodal interfaces in intelligent workspaces. The system is based on a stereo vision system and provides a series of mechanisms for an efficient segmentation of the arm-hand structure over the screen and its description in terms of moments that can be used by a neural network based structure in order to provide position and gesture classification results. These can be adapted to the user's desires through an interaction and feedback mechanism permitting a natural mutual learning process between the system and the human.
['Abraham Prieto', 'Francisco Bellas', 'Richard J. Duro', 'Fernando López-Peña']
An Adaptive Visual Gesture Based Interface for Human Machine Interaction in Intelligent Workspaces