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I'm trying to use opencv to implement a feature in my app. Basically, my app allows users to authenticate by using their face. Live video will be captured and frames are extracted. Using these extracted images, the model is learned. Next time when a user logs in, frames are sent to the model for deciding if this is the authenticated user.

I found this example from opencv site which uses FaceRecognizer. However, they use an existing dataset with 10 classes (10 persons). In my case, only one class is considered (Or we can consider two classes including the authenticated user and unknown users). Could you please suggest me a solution? Thank you.

lenhhoxung
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1 Answers1

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First of all, I would suggest you look at other methods for face recognition (DNN-based) since the OpenCV FaceRecognizer stuff (ex eigen) is not particularly good.

However, if you want to use it, note that FaceRecognizer::predict has an overload that outputs a "confidence" value. This is the value you would need to look at to decide if the match was right. You'll need to experiment to find your sweet spot between false positives and false negatives.

logidelic
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