sixFaces | R Documentation |
sixFaces
:
The 230*240 = 55,200 pixels pictures of six faces (3 men and 3 women).
To be used to illustrate PCA or PLS on images.
data("sixFaces")
A list containing 3 objects:
face.array.raw
a 230 * 240 * 6 array storing the 6
(230 by 240 pixels) raw images of the faces.
Values of the pixels
go from 0 to 253.
face.array.normed
a 230 * 240 * 6 array storing the 6
(230 by 240 pixels) normalized images of the faces.
The sum of the squared values of a normalized image is now equal to 1.
face.matrix
a matrix of dimensions 6 by 55,220 ( = 230*240)
storing the vectorized (normalized) pictures of the faces.
sixFaces
contains the original pictures
(as a 230 * 240 * 6 array),
the normalized pictures of the faces (such that the sum of squares
of the pixels of a face is equal to 1), the
6*55,200 matrix of the faces.
To get back a 230*240 image-matrix from the vectorized version of the face use, for example:
face1 <- matrix(face.matrix[1,],230,240,byrow = FALSE)
To visualize an image use, for example:
image(sixFaces$face.array.normed[,,1])
To fold back an image from the vectorized and vizualize it, use:
image(matrix(sixFaces$face.matrix[1,],230,240,byrow = FALSE))
Hervé Abdi
The faces have been used in a few publications including:
Abdi, H., Valentin, D., O'Toole, A.J., & Edelman, B. (2005). DISTATIS: The analysis of multiple distance matrices. Proceedings of the IEEE Computer Society: International Conference on Computer Vision and Pattern Recognition. (San Diego, CA, USA). pp. 42-47.
Abdi, H., & Valentin, D. (2006). Mathématiques pour les Sciences Cognitives, (Mathematics for Cognitive Sciences). Grenoble (France): Presses Universitaires de Grenoble.
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