Enumerate the facial features of asian
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Enumerate the facial features of asian
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Answer:
#Ⓒⓐⓡⓡⓨⓞⓝⓛⓔⓐⓡⓝⓘⓝⓖ
Study it First he-he-he
Explanation:
The facial region segmentation is based on the distance between irises (ED) and its relation with the rest of regions
[9], where dimensions of each region are defined by 2ED(width)x0.75ED(height), 1.2EDx0.65ED and 1.7EDx0.5ED
for regions of eyes-eyebrows, mouth and nose respectively. Figure 1 shows an example of facial region segmentation.
The PCA algorithm is applied independently to each facial region, thus three Eigenspaces based on each of the
three regions are obtained. This method enables us to combine independent feature vectors in order to process
information from more than one facial region. The procedure for obtaining each independent Eigenspace begins with
the conversion of the facial region images into column vectors, thence each image can be treated as a separate 1-
dimensional array of pixel values. Subsequently, PCA employs the covariance matrix of the complete set of facial
region images under analysis for obtaining its eigenvectors which finally will define the Eigenspace as principal
components. Finally, the feature vectors per facial region are just projections of the 1-dimensional array of the original
facial region image into its respective Eigenspace. The process of independent feature vectors estimation, as well as
an example of 3 region feature vector combination, are shown in Figure 2, where ES_e, ES_m and ES_n represent the
Eigenspaces for eyes-eyebrows, mouth and nose region respectively.