Description:
Celebrities in Frontal-Profile Wild (CPFW) dataset contains images of 500 subjects (with 10 frontal images and 4 profile images for each subject). 5000 frontal images were pre-processed using D-lib to crop and align the faces. 37 images had a failure to detect (FTD) case. The final gallery had the following distribution of # the number of images /subject.
#subjects, #images
6 8
25 9
469 10
total images= 4963
total subjects= 500

To simplify calculations, 6 images per subject are used for this assignment.

You should assume the system is symmetric. You may use the programming language/tool of your choice (R, Python, Matlab, etc) in the analysis of the data. Please indicate which tool/language is being used, and include a text file of code with your submission.

Files needed for this assignment (see Module 2):

Answer the following Question:

Determine the total number of scores that can be generated. (You may assume 6 images/subject)
How many imposter (non-mated) scores can be generated? How many are genuine (mated)? (Again, assume 6 images/subject)
Generate a minimum set of 100 thresholds, and determine the FAR and FRR at each threshold value.
Plot the ROC Curve for your data (FRR vs. FAR) and (TAR vs. FAR).
Using eq. 1.9 from the book, compute the AUC of the system?