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What's the state of the art in terms of extending such systems to handle faces that are partially obscured (e.g. wearing glasses)? References to further resources in the area accepted and appreciated! I'm going to start work on a face recognition system soon and I'm keen to learn more about their current limitations.

It's just an issue of training. I'd expect a similar setup as I describe could be used to associate a series of faces with and without different things attached to their face, and a neural net could be trained to generate, for example, a no eye glasses wearing image from one with eye glasses. We already do that with facial expressions. I think the issues to be improved upon are extending the recognition beyond the face - include ear characteristics to extend recognition beyond +/- 30 degrees, and although my lab tells me analyzing gait is a dead end, I feel there might be something there that can help. Also lighting neutralization is an area that needs some help, which includes illumination balancing without removing important details, shadow removal, and colored illumination white balancing.

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