Hitherto, one major challenge to sign language recognition is how to develop approaches that scale well with increasing vocabulary size. In large vocabulary speech recognition realm, it is effective to use phonemes instead of words as the basic units. This idea can be used in large vocabulary Sign Language recognition, too. In this paper, Etyma are defined to be the smallest unit in a sign lang...

This paper presents an overview of current work on the recognition of sign language and a prototype of a simple editor for a small subset of the Brazilian Sign Language, LIBRAS. Handshape based alphabetical signs, are captured by a single digital camera, processed on-line by using computational vision techniques and converted to the corresponding Latin letter. The development of such prototype ...

The manual signs in sign languages are generated and interpreted using three basic building blocks: handshape, motion, and place of articulation. When combined, these three components (together with palm orientation) uniquely determine the meaning of the manual sign. This means that the use of pattern recognition techniques that only employ a subset of these components is inappropriate for inte...

Automatic sign language recognition (ASLR) is a special case of automatic speech recognition (ASR) and computer vision (CV) and is currently evolving from using artificial labgenerated data to using ’real-life’ data. Although ASLR still struggles with feature extraction, it can benefit from techniques developed for ASR. We present a large-vocabulary ASLR system that is able to recognize sentenc...

In this paper, a novel scheme for representing symbolic images in a symbolic image database (SID) is proposed. The proposed scheme is based on triangular spatial relationship (TSR) [Pattern Recognition Lett. 22 (2001) 999]. The scheme preserves TSR among the components in a symbolic image by the use of quadruples. A SID is created through the construction of B-tree, an efficient multilevel inde...