Show HN: OpenFace – Face recognition with Google's FaceNet deep neural network

This depends on what you want to use face recognition for. Maybe I should say more clearly in the README who this project is for. I could have released trained classifiers on 10,000 celebrities, but I focused the projects towards providing an easy way to train new classifiers with small amounts of data. I think this direction allows for more people to use and benefit from the library.

For example, check out our YouTube video of a demo training a classifier in real-time with just 10 images per person at https://www.youtube.com/watch?v=LZJOTRkjZA4. This demo is included in the repo and the README has instructions on running it.

Also note that there is a distinction between training the neural network, which extracts the face representations, from using the features for tasks like clustering and classification.

Yes, the processing pipeline first does face detection and a simple transformation to normalize all faces to 96x96 RGB pixels. Then each face is passed into the neural network to get a 128 dimensional representation on the unit hypersphere.

For a landscape, face detection would probably not find any faces and the neural network wouldn't be called.

And an image with multiple people will have many outputs: the bounding boxes of faces and associated representations.

Summary: OpenFace uses fundamentally different techniques (a deep neural network) for face recognition that OpenBR currently doesn't provide.

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As our initial ROC curve on LFW's similarity benchmark in https://github.com/cmusatyalab/openface/blob/master/images/n... shows, this approach results in slightly improved performance. The best point is an FPR of 0.0 and TPR of 1.0 (top left). You can see today's state-of-the-art private systems in the top left, followed by open source systems, then by historical techniques OpenCV provides like Eigenfaces. The dashed line in the middle shows what randomly guessing would provide.

OpenBR is going in a great direction for reproducible and open face recognition. They provide a pipeline for preprocessing and representing faces, as well as doing similarity and classification tasks on the representations. The techniques from OpenFace could be integrated into OpenBR's pipeline.