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

Awad, George

 
9783639126587: A Framework for Sign Language Recognition: Applying Support Vector Machines and Active Learning for Skin Segmentation and Boosted Temporal Sub-units for Recognition
Softcover
ISBN 10: 3639126580 ISBN 13: 9783639126587
Verlag: VDM Verlag Dr. Müller, 2010

Inhaltsangabe

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 using a boosting framework. In brief, This book takes you into a journey and describes all the necessary steps that are needed to recognize the meaning of a performed signs in a video.

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Reseña del editor

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 using a boosting framework. In brief, This book takes you into a journey and describes all the necessary steps that are needed to recognize the meaning of a performed signs in a video.

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Verlag
VDM Verlag Dr. Müller
Erscheinungsdatum
2010
Sprache
Englisch
ISBN 10 
3639126580
ISBN 13 
9783639126587
Einband
Tapa blanda
Anzahl der Seiten
172
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Verantwortliche Person
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