Abstract. A sign language recognition system based on Hidden Markov Models(HMMs) and Auto-regressive Hidden Markov Models(ARHMMs) has been proposed in this paper. ARHMMs fully cons...
Xiaolin Yang, Feng Jiang, Han Liu, Hongxun Yao, We...
Recognition of signs in sentences requires a training
set constructed out of signs found in continuous sentences.
Currently, this is done manually, which is a tedious process.
I...
Abstract. This paper addresses an aspect of sign language (SL) recognition that has largely been overlooked in previous work and yet is integral to signed communication. It is the ...
Although facial features are considered to be essential for humans to understand sign language, no prior research work has yet examined their significance for automatic sign langu...
Ulrich von Agris, Moritz Knorr, Karl-Friedrich Kra...
This paper describes a referential semantic language model that achieves accurate recognition in user-defined domains with no available domain-specific training corpora. This mo...