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

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: some can be predefined for supervised learning, some need self-organisation, some need generative models to be learned. Generative models may offer strong advantages in cases where a higher degree of generalization is needed. They have 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 (RBF) and a generative one (RGBN) both extended in a time-delay version

Lecture Notes in Computer Science 1 Comparison of Feedforward (TDRBF) and Generative (TDRGBN) Network for Gesture Based Control

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 in cases where a higher degree of generalization is needed. They have 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.