Facial Feature Tracking and Expression Recognition for Sign Language. Automatic recognition of common facial gestures in sign languages using single camera input

Facial Feature Tracking and Expression Recognition for Sign Language. Automatic recognition of common facial gestures in sign languages using single camera input

?smail Ar?, Lale Akarun

     

бумажная книга



Издательство: Книга по требованию
Дата выхода: июль 2011
ISBN: 978-3-8383-2713-6
Объём: 96 страниц
Масса: 166 г
Размеры(В x Ш x Т), см: 23 x 16 x 1

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.

Данное издание не является оригинальным. Книга печатается по технологии принт-он-деманд после получения заказа.

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