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    • Markham, Charles (11)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 11 of 11 1 Ghost Towns: Semantically Labelled Object Removal From Video Clifford, William; Markham, Charles. - 2019 BASE Show details 2 Weakly Supervised Training of a Sign Language Recognition System Using Multiple Instance Learning Density Matrices Kelly, Daniel; McDonald, John; Markham, Charles. - : IEEE, 2011 BASE Show details 3 A person independent system for recognition of hand postures used in sign language Kelly, Daniel; McDonald, John; Markham, Charles. - : Elsevier, 2010 BASE Show details 4 Evaluation of Threshold Model HMMs and Conditional Random Fields for Recognition of Spatiotemporal Gestures in Sign Language Kelly, Daniel; McDonald, John; Markham, Charles. - : IEEE, 2009 BASE Show details 5 Recognizing Spatiotemporal Gestures and Movement Epenthesis in Sign Language Kelly, Daniel; McDonald, John; Markham, Charles. - : IEEE, 2009 BASE Show details 6 Continuous recognition of motion based gestures in sign language Kelly, Daniel; McDonald, John; Markham, Charles. - : IEEE, 2009 BASE Show details 7 Automatic Recognition of Head Movement Gestures in Sign Language Sentences Kelly, Daniel; Reilly Delannoy, Jane; McDonald, John. - : Dept. of Computer Science, National University of Ireland, Maynooth, 2009 BASE Show details 8 A Framework for Continuous Multimodal Sign Language Recognition Kelly, Daniel; Delannoy, Jane Reilly; McDonald, John; Markham, Charles. - : ACM, 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. URL: http://mural.maynoothuniversity.ie/8338/ http://mural.maynoothuniversity.ie/8338/1/JM-Framework-2009.pdf BASE Hide details 9 Incorporating Facial Features into a Multi-Channel Gesture Recognition System for the Interpretation of Irish Sign Language Sequences Kelly, Daniel; Delannoy, Jane Reilly; McDonald, John. - : IEEE, 2009 BASE Show details 10 Analysis of Sign Language Gestures Using Size Functions and Principal Component Analysis Kelly, Daniel; McDonald, John; Lysaght, Thomas. - : IEEE, 2008 BASE Show details 11 A system for teaching sign language using live gesture feedback Kelly, Daniel; McDonald, John; Markham, Charles. - : IEEE, 2008 BASE Show details

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