A Framework for Sign Language Recognition: Applying Support Vector Machines and Active Learning for Skin Segmentation and Boosted Temporal Sub-units for Recognition

A Framework for Sign Language Recognition: Applying Support Vector Machines and Active Learning for Skin Segmentation and Boosted Temporal Sub-units for Recognition
Автор
 
Год
 
Страниц
 
172
ISBN
 
3639126580
Категория
 
Поступления - 2010 г. - Июнь.

Описание:

This book 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 (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. 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. We propose a novel algorithm to model and segment these subunits, then try to learn the informative combinations of subunits/features...

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