Visual Sign Language Recognition
Eun‐Jung Holden, Robyn Owens, Gilles Roy · 1999
We have developed the Hand Motion Understanding (HMU) system that understands static and dynamic signs of the Australian Sign Language (Auslan). The HMU system uses a visual 3D hand tracker for motion sensing, and an adaptive fuzzy expert system for classification of the signs. This paper presents the hand tracker that extracts 3D hand configuration data with 21 degrees-of-freedom (DOFs) from a motion sequence that is captured from a single viewpoint, with the aid of a colour-coded glove. The tracker is used for the training and evaluation of the HMU system with 22 static and dynamic signs. Before training the HMU system recognised 20 signs, and after training, it recognised 21 signs. 1. Introduction Automated gesture recognition has been an active area of research in human-computer interaction applications and sign language translation systems. The gesture recognition may be performed in two stages: the motion sensing, which extracts useful motion data from the actual motion input; a...