  Sign language recognition is a difficult task, yet required for many
applications in real-time speed. Using RGB cameras for recognition of sign
languages is not very successful in practical situations and accurate 3D
imaging requires expensive and complex instruments. With introduction of
Time-of-Flight (ToF) depth cameras in recent years, it has become easier to
scan the environment for accurate, yet fast depth images of the objects without
the need of any extra calibrating object. In this paper, a robust system for
sign language recognition using ToF depth cameras is presented for converting
the recorded signs to a standard and portable XML sign language named SiGML for
easy transferring and converting to real-time 3D virtual characters animations.
Feature extraction using moments and classification using nearest neighbor
classifier are used to track hand gestures and significant result of 100% is
achieved for the proposed approach.
