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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; Markham, Charles. - : Dept. of Computer Science, National University of Ireland, Maynooth, 2009 Abstract: A novel system for the recognition of head movement gestures used to convey non-manual information in sign language is presented. We propose a framework for recognizing a set of head movement gestures and identifying head movements outside of this set. Experiments show our proposed system is capable of classifying three different head movement gestures and identifying 15 other head movements as movements which are outside of the training set. In this paper we perform experiments to investigate the best feature vectors for discriminating between positive a negative head movement gestures and a ROC analysis of the systems classifications performance showed an area under the curve measurement of 0:936 for the best performing feature vector. Keyword: Computer Science URL: http://mural.maynoothuniversity.ie/2548/3/DK_Automatic_Recognition.pdf http://mural.maynoothuniversity.ie/2548/ BASE Hide details 8 A Framework for Continuous Multimodal Sign Language Recognition Kelly, Daniel; Delannoy, Jane Reilly; McDonald, John. - : ACM, 2009 BASE Show 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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