Recovering the linguistic components of the manual signs in American Sign Language

Abstract

Manual signs in American sign language (ASL) are constructed using three building blocks -handshape, motion, and place of articulations. Only when these three are successfully estimated, can a sign by uniquely identified. Hence, the use of pattern recognition techniques that use only a subset of these is inappropriate. To achieve accurate classifications, the motion, the handshape and their three-dimensional position need to be recovered. In this paper, we define an algorithm to determine these three components form a single video sequence of two-dimensional pictures of a sign. We demonstrated the use of our algorithm in describing and recognizing a set of manual signs in ASL.