Abstract
This paper proposes one approach for eye contour extraction and parameterization from monkey face in the monocular image. The possible face regions are first segmented using facial skin color model based on YCbCr color space. The color model is constructed from many collected sample pixels of face regions, and Gaussian Mixture Model is used to represent the distribution of color points. Then the segmented regions are further processed with the help of mathematical morphology operations to locate the face region. The face is size normalized according to face width, and rotation normalized according to two located eyes. Taking the boundaries of eye as initial point set, ACM is adopted to search for more smooth and continuous eye contours. Points on the extracted eye contours are used to fit the quadratic curve with least-squares fitting method. Based on the parameters of quadratic function, angry and calm expressions of monkey face are recognized. Our method can be used for facial expression recognition and emotion decision, which is very helpful for medical science research often taking monkey as the experimental object.
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Zhang, D. et al. (2010). Extraction and Parameterization of Eye Contour from Monkey Face in Monocular Image. In: Luo, Q. (eds) Advancing Computing, Communication, Control and Management. Lecture Notes in Electrical Engineering, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05173-9_24
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DOI: https://doi.org/10.1007/978-3-642-05173-9_24
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