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davidsandberg / facenet

Face recognition using Tensorflow
MIT License
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Euclidean distance not a good way to compare? #770

Open jax79sg opened 6 years ago

jax79sg commented 6 years ago

Hi,

I used a small subset of LFW faces and performed a detection (crop) before feed forwarding the images into the most recent model trained with WebFaces. Next i do a pairwise Euclidean distance of each embedding and generated the attached chart. What the chart says is that both similar and dissimilar faces occupy the same distance range. How would one use distance to determine if there is a match? I also tried a KNN on the embeddings and was given a 3% accuracy. Is alignment a necessity for FaceNet?

Thank you. facenetcroppedraw facenetcroppedbw

rain2008204 commented 6 years ago

@jax79sg maybe the Euclidean distance is not a good way ,so how do you solve this problem?

LCorleone commented 6 years ago

alignment is necessary!

jax79sg commented 6 years ago

Hi @LCorleone,

Thanks for the reply. I had actually deployed this on Android but has yet to find a good way to align it on Android. Would you have any recommendations?

iamrishab commented 3 years ago

alignment is necessary!

Even alignment doesn't help much.