| 23 |
Coke is It: How Stories in Childhood Memories Illuminate an Icon
|
|
|
|
BASE
|
|
Show details
|
|
|
| 24 |
The TRECVid 2008 BBC rushes summarization evaluation
|
|
|
|
In: Over, Paul, Smeaton, Alan F. and Awad, George M. (2008) The TRECVid 2008 BBC rushes summarization evaluation. In: TVS 2008 - TRECVID BBC Rushes Summarization Workshop, Oct 27 - Nov 1 2008, Vancouver, BC, Canada. ISBN 978-1-60558-303-7 (2008)
|
|
BASE
|
|
Show details
|
|
|
| 25 |
A framework for sign language recognition using support vector machines and active learning for skin segmentation and boosted temporal sub-units
|
|
|
|
In: Awad, George M. (2007) A framework for sign language recognition using support vector machines and active learning for skin segmentation and boosted temporal sub-units. PhD thesis, Dublin City University. (2007)
|
|
Abstract:
This dissertation describes new techniques that can be used in a sign language recognition (SLR) system, and more generally in human gesture systems. Any SLR system consists of three main components: Skin detector, Tracker, and Recognizer. The skin detector is responsible for segmenting skin objects like the face and hands from video frames. The tracker keeps track of the hand location (more specifically the bounding box) and detects any occlusions that might happen between any skin objects. Finally, the recognizer tries to classify the performed sign into one of the sign classes in our vocabulary using the set of features and information provided by the tracker. In this work, we propose a new technique for skin segmentation using SVM (support vector machine) active learning combined with region segmentation information. Having segmented the face and hands, we need to track them across the frames. So, we have developed a unified framework for segmenting and tracking skin objects and detecting occlusions, where both components of segmentation and tracking help each other. Good tracking helps to reduce the search space for skin objects, and accurate segmentation increases the overall tracker accuracy. Instead of dealing with the whole sign for recognition, the sign can be broken down into elementary subunits, which are far less in number than the total number of signs in the vocabulary. This motivated us to propose a novel algorithm to model and segment these subunits, then try to learn the informative combinations of subunits/features using a boosting framework. Our results reached above 90% recognition rate using very few training samples.
|
|
Keyword:
Machine learning; segmentation; sign language recognition system; slr; support vector machine; svm; tracking
|
|
URL: http://doras.dcu.ie/16936/
|
|
BASE
|
|
Hide details
|
|
|
| 27 |
Zẅiˀi ni fuŋə̀ nki ŋwàˀnə̀ Àshwəŋnə̀ Pìnyinə (Learn to read and write the Pinyin language)
|
|
|
|
BASE
|
|
Show details
|
|
|
| 28 |
A unified system for segmentation and tracking of face and hands in sign language recognition
|
|
|
|
In: Awad, George M., Han, Junwei and Sutherland, Alistair (2006) A unified system for segmentation and tracking of face and hands in sign language recognition. In: ICPR 2006 - 18th International Conference on Pattern Recognition, 20-24 August 2006, Hong Kong, China. (2006)
|
|
BASE
|
|
Show details
|
|
|
| 29 |
General chemistry students’ understanding of structure-function relationships
|
|
|
|
In: http://chemed.chem.purdue.edu/chemed/bodnergroup/PDF_2008/85+Shane.pdf (2006)
|
|
BASE
|
|
Show details
|
|
|
| 33 |
Indiana high school science teachers' beliefs about the intended and actual impacts of standards-based reforms
|
|
|
|
In: Theses and Dissertations Available from ProQuest (2005)
|
|
BASE
|
|
Show details
|
|
|
| 34 |
The Spanish heritage language learning experience in the rural midwest: voices from a newly diverse small town
|
|
|
|
BASE
|
|
Show details
|
|
|
| 36 |
Knowledge Representation and Reasoning for Mixed-Initiative Planning
|
|
|
|
BASE
|
|
Show details
|
|
|
|
|
