But in the OpenCV, the algorithm exists for that purpose directly.
The currently available algorithms are:
Eigenfaces (see createEigenFaceRecognizer())
Fisherfaces (see createFisherFaceRecognizer())
Local Binary Patterns Histograms (see createLBPHFaceRecognizer())
These algorithms assume we must given a set of images belong to some different people, and judge the given images is similar to which person we given before.
(Because the training data set is small(only one image), so I choose the Local Binary Patterns Histogram)
I may train the algorithm by a image of one person and some meaningless images(images without face), and the result must say the test image is most similar to the only person of our training set and we can just output the confidence of result.
It's just so dirty to adapt the algorithm to my purpose. I just wonder, is there any elegant way to implement it?