Comparison of Feedforward (TDRBF) and Generative (TDRGBN) Network for Gesture Based Control

Authors:
Helen Vassilakis;A. Jonathan Howell;Hilary Buxton
Affiliations:
-;-;-
Venue:
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Year:
2001

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Abstract

In Visually Mediated Interaction (VMI) there is a range of tasks that need to be supported (face and gesture recognition, camera controlled by gestures, visual interaction etc). These tasks vary in complexity. Generative and self-organising models may offer strong advantages over feedforward ones in cases where a higher degree of generalization is needed. They have the ability to model the density function that generates the data, and this gives the potential of "understanding" the gesture independent from the individual differences on the performance of a gesture. This paper presents a comparison between a feedforward network (RBFN) and a generative one (RGBN) both extended in a time-delay version.