Facial expression recognition: A comparison between static and dynamic approaches
The identification of facial expressions with human emotions plays a key role in non-verbal human communication and has applications in several areas. In this work, we analyze two approaches for expression recognition. One of them is a staticbased appearance method. In this approach, a binary-based...
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| Autores principales: | , , |
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2016
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS16339_v2016_n2_p_Iglesias http://hdl.handle.net/20.500.12110/paper_NIS16339_v2016_n2_p_Iglesias |
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| Sumario: | The identification of facial expressions with human emotions plays a key role in non-verbal human communication and has applications in several areas. In this work, we analyze two approaches for expression recognition. One of them is a staticbased appearance method. In this approach, a binary-based descriptor, denominated Oriented Fast and Rotated BRIEF (ORB), is used on a single frame of a sequence of images to extract texture information, and classified with a Support Vector Machine. The other is a dynamic approach introducing a new simple descriptor based on the angles formed by the landmarks to capture the dynamic of the gesture on an image sequence. In this case the recognition is performed by a Conditional Random Field (CRF) classifier. The paper compares both methodologies, analyze their similarities and differences. |
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