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Facial Feature Tracking and Expression Recognition for Sign Language: Automatic recognition of common facial gestures in sign languages using single camera input - Softcover
The focus of this work is on classifying the most common non-manual (facial) gestures in Sign Language. This goal is achieved in two consecutive steps: First, automatic facial landmarking is performed based on Multi-resolution Active Shape Models (MRASMs). Second, the tracked landmarks are normalized and expression classification is done based on multivariate Continuous Hidden Markov Model (CHMMs). We collected a video database of expressions from Turkish Sign Language (TSL) to test the proposed approach. The expressions used are universal and the results are applicable to other sign languages. Single view vs. multi-view and person specific vs. generic MRASM trackers are compared both for tracking and expression recognition. The multi-view person-specific tracker performs the best and tracks the landmarks robustly. For expression classification, the proposed CHMM classifier is tested on different training and test set combinations and the results are reported. We observe that the classification performances of distinct classes are very high.
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- PublisherLAP Lambert Academic Publishing
- Publication date2009
- ISBN 10 3838327136
- ISBN 13 9783838327136
- BindingPaperback
- Number of pages96
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Facial Feature Tracking and Expression Recognition for Sign Language
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LAP LAMBERT Academic Publishing Sep 2010
(2010)
ISBN 10: 3838327136
ISBN 13: 9783838327136
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Book Description Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The focus of this work is on classifying the most common non-manual (facial) gestures in Sign Language. This goal is achieved in two consecutive steps: First, automatic facial landmarking is performed based on Multi-resolution Active Shape Models (MRASMs). Second, the tracked landmarks are normalized and expression classification is done based on multivariate Continuous Hidden Markov Model (CHMMs). We collected a video database of expressions from Turkish Sign Language (TSL) to test the proposed approach. The expressions used are universal and the results are applicable to other sign languages. Single view vs. multi-view and person specific vs. generic MRASM trackers are compared both for tracking and expression recognition. The multi-view person-specific tracker performs the best and tracks the landmarks robustly. For expression classification, the proposed CHMM classifier is tested on different training and test set combinations and the results are reported. We observe that the classification performances of distinct classes are very high. 96 pp. Englisch. Seller Inventory # 9783838327136
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Facial Feature Tracking and Expression Recognition for Sign Language : Automatic recognition of common facial gestures in sign languages using single camera input
Published by
LAP LAMBERT Academic Publishing
(2009)
ISBN 10: 3838327136
ISBN 13: 9783838327136
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Book Description Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The focus of this work is on classifying the most common non-manual (facial) gestures in Sign Language. This goal is achieved in two consecutive steps: First, automatic facial landmarking is performed based on Multi-resolution Active Shape Models (MRASMs). Second, the tracked landmarks are normalized and expression classification is done based on multivariate Continuous Hidden Markov Model (CHMMs). We collected a video database of expressions from Turkish Sign Language (TSL) to test the proposed approach. The expressions used are universal and the results are applicable to other sign languages. Single view vs. multi-view and person specific vs. generic MRASM trackers are compared both for tracking and expression recognition. The multi-view person-specific tracker performs the best and tracks the landmarks robustly. For expression classification, the proposed CHMM classifier is tested on different training and test set combinations and the results are reported. We observe that the classification performances of distinct classes are very high. Seller Inventory # 9783838327136
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Facial Feature Tracking and Expression Recognition for Sign Language
Published by
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ISBN 13: 9783838327136
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Book Description Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ari IsmailIsmail Ari is a PhD student at Bogazici University, Turkey, where he received his BSc and MSc degrees in 2006 and 2008, respectively. Lale Akarun has been a full professor at Computer Engineering Department of Bogazici Un. Seller Inventory # 5413342
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Facial Feature Tracking And Expression Recognition For Sign Language: Automatic Recognition Of Common Facial Gestures In Sign Languages Using Single Camera Input
Published by
Lap Lambert Academic Publishing
(2009)
ISBN 10: 3838327136
ISBN 13: 9783838327136
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Book Description Paperback. Condition: Brand New. 96 pages. 8.66x5.91x0.22 inches. In Stock. Seller Inventory # zk3838327136
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