Real-time recognition of hand alphabet gestures using principal component analysis
Henrik Birk, Thomas Baltzer Moeslund, Claus Brøndgaard Madsen · 1997
This work presents a design for a human computer interface capable of recognizing 25 gestures from the international hand alphabet in real-time. Principal Component Analysis (PCA) is used to extract features from images of gestures. The features represent gesture images in terms of an optimal coordinate system, in which the classes of gestures make up clusters. The system is divided into two parts: an off-line and an on-line part.