python - Face comparison (Not recognition or detection) using OpenCV and Keras? -


first of here github link question.

and here question:

i face comparison function using python. , can successfully(?) recognize faces using opencv. now, how do comparison thing?

what understand this:

in general machine learning approach, need gather lots of data particular person , finalize using cnn.

however, got 2 images, how do comparison? should think in terms of classification or clustering (using knn)?

thank in advance help.

you can use idea of face-embeddings, example proposed in highly-cited paper facenet , implemented in openface (which comes pre-trained).

the general idea: take preprocessed face (frontal, cropped, ...) , embedd lower dimension characteristic, similar faces in input should have low euclidean-distance in output.

so in case: use embedding-cnn map faces reduced space (usually vector of size 128) , calculate distance in euclidean-space. of course cluster faces then, that's not task.

the thing here besides general idea: openface nice implementation ready use , it's homepage explains idea:

use deep neural network represent (or embed) face on 128-dimensional unit hypersphere.

the embedding generic representation anybody's face. unlike other face representations, embedding has nice property larger distance between 2 face embeddings means faces not of same person.

this property makes clustering, similarity detection, , classification tasks easier other face recognition techniques euclidean distance between features not meaningful.

they have comparison-demo here.


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