Tracking Facial Expressions by Using Stereoscopy Video and Back Propagation Neural Network

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Título :	Tracking Facial Expressions by Using Stereoscopy Video and Back Propagation Neural Network
Palabras clave :	Facial expression Backpropagation neural networks VJ method Nitzberg algorithm
Fecha de publicación :	16-ene-2013
Editorial :	Kathmandu University Journal of Science, Engineering and Technology
Descripción :	In this paper we propose a method to tracking facial expressions. A system with two cameras is used to capture stereoscopic video sequences. The frames are acquired and analyzed by matching two stereoscopic frames through a correlation method that performs image processing to obtain a resulting frame, and then it is processed to recognize a human face by using the Viola and Jones (VJ) method. The face is located via the Nitzberg operator and it provides the feature points of the eyes, eyebrows, nose and mouth, which are introduced into a Backpropagation neural network that is capable of learning and classifying different types of facial expressions that make a person, feel such as: surprised, scared, unhappy, sad, mad and happy. Finally, the result of this process is recognition of facial expressions. Kathmandu University
URI :	http://www.repositoriodigital.ipn.mx/handle/123456789/10584
Otros identificadores :	Vol. 6, No. 1, March 2010 1816-8752 http://hdl.handle.net/123456789/41
Aparece en las colecciones:	Doctorado

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