Face Detection and Modeling for Recognition - Biometrics Research ...

5.14 Fine alignment using geodesic active contours: (a) a generic cartoon face
constructed from interacting snakes; (b) to (f) for five different subjects.
For each subject, the image in the first row is the captured face
image; the second row shows semantic face graphs obtained after coarse
alignment, and overlaid on the color image; the third row shows semantic
face graphs with individual components shown in different shades
of gray; the last row shows face graphs with individual components
after fine alignment. . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
5.15 A semantic face matching algorithm. . . . . . . . . . . . . . . . . . . . . 134
5.16 Five color images (256 × 384) of a subject. . . . . . . . . . . . . . . . . . 135
5.17 Face images of ten subjects. . . . . . . . . . . . . . . . . . . . . . . . . . 135
5.18 Examples of misclassification: (a) input test image; (b) semantic face
graph of the image in (a); (c) face graph of the misclassified subject;
(d) face graph of the genuine subject obtained from the other images
of the subject in the database (i.e., without the input test image in
(a)). Each row shows one example of misclassification. . . . . . . . . 137
5.19 Cartoon faces reconstructed from Fourier descriptors using all the frequency
components: (a) to (j) are ten average cartoon faces for ten
different subjects based on five images for each subject. Individual
components are shown in different shades in (a) to (e). . . . . . . . . 138
5.20 Cartoon faces reconstructed from Fourier descriptors using only 50% of
the frequency components: (a) to (j) are ten average cartoon faces for
ten different subjects based on five images for each subject. Individual
components are shown in different shades in (a) to (e). . . . . . . . . 139
5.21 Cartoon faces reconstructed from Fourier descriptors using only 30% of
the frequency components: (a) to (j) are ten average cartoon faces for
ten different subjects based on five images for each subject. Individual
components are shown in different shades in (a) to (e). . . . . . . . . 139
5.22 Facial caricatures generated based on a generic 3D face model: (a) a prototype
of the semantic face graph, G 0 , obtained from a generic 3D face
model, with individual components shaded; (b) face images of six different
subjects; (c)-(g) caricatures of faces in (b) (semantic face graphs
with individual components shown in different shades) with different
values of exaggeration coefficients, k, ranging from 0.1 to 0.9. . . . . . 141
5.23 Facial caricatures generated based on the average face of 50 faces (5 for
each subject):(a) a prototype of the semantic face graph, G 0 , obtained
from the mean face of the database, with individual components
shaded; (b) face images of six different subjects; (c)-(g) caricatures of
faces in (b) (semantic face graphs with individual components shown
in different shades) with different values of exaggeration coefficients, k,
ranging from 0.1 to 0.9. . . . . . . . . . . . . . . . . . . . . . . . . . . 142
6.1 A prototype of a face identification system with the tracking function. . . 148
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