Tracking Facial Expressions by Using Stereoscopy Video and Back Propagation Neural Network
2013
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.
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