Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets

Gesture recognition is a difficult task in computer vision due to the numerous degrees of freedom of a human hand. Fortunately, human gesture covers only a small part of the theoretical "configuration space" of a hand, so an appearance based representation of human gesture becomes tractable. A major problem, however, is the acquisition of appropriate labelled image data from which an appearance based representation can be built. In this paper we apply self-organising maps for a visualisation of large amounts of segmented hands performing pointing gestures. Using a graphical interface, an easy labelling of the data set is facilitated. The labelled set is used to train a neural classification system, which is itself embedded in a larger architecture for the recognition of gestural reference to objects.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Axel Saalbach, Gunther Heidemann, Holger Bekel, Ingo Bax
• Keywords: Appearance Based Representation, Computer Vision, Gesture Recognition, Human Gesture, ICPR 2004