Book Chapter


Charles Markham
John McDonald
Jane Reilly Delannoy
Daniel Kelly


Computer Science

single continuous sign language detection recognition head movements hand sign language recognition

A Framework for Continuous Multimodal Sign Language Recognition (2009)

Abstract We present a multimodal system for the recognition of manual signs and non-manual signals within continuous sign language sentences. In sign language, information is mainly conveyed through hand gestures (Manual Signs). Non-manual signals, such as facial expressions, head movements, body postures and torso movements, are used to express a large part of the grammar and some aspects of the syntax of sign language. In this paper we propose a multichannel HMM based system to recognize manual signs and non-manual signals. We choose a single non-manual signal, head movement, to evaluate our framework when recognizing non-manual signals. Manual signs and non-manual signals are processed independently using continuous multidimensional HMMs and a HMM threshold model. Experiments conducted demonstrate that our system achieved a detection ratio of 0.95 and a reliability measure of 0.93.
Collections Ireland -> Maynooth University -> Type = Book Section
Ireland -> Maynooth University -> Academic Unit = Faculty of Science and Engineering
Ireland -> Maynooth University -> Status = Published
Ireland -> Maynooth University -> Open Access DRIVERset
Ireland -> Maynooth University -> Academic Unit = Faculty of Science and Engineering: Computer Science

Full list of authors on original publication

Charles Markham, John McDonald, Jane Reilly Delannoy, Daniel Kelly

Experts in our system

Charles Markham
Maynooth University
Total Publications: 64
John McDonald
Maynooth University
Total Publications: 79
Daniel Kelly
University College Cork
Total Publications: 17