"Quick and Dirty" Facial Recognition and Database Storage/Lookup in Java

For the last week I've been researching and exper开发者_JAVA技巧imenting with facial recognition. The intended application is for a person to be able to look up a person's information in a database (SQL) by simply taking a picture of their face. The initial expectation was to be able to compress a face down to a key or hash and use this as the database lokup. This need not be extremely accurate as the person looking up the information can and most likely will end up doing a final comparison between the original image on file and the person standing in front of them.

OpenCV/JavaCV seems to be the obvious starting point, and the facial detection that it provides works well, however the implementation of Eigenfaces for facial recognition isn't ideal because online training by recompiling hundreds of thousands of user faces every time a new face needs to be added to the training set wouldn't work.

I am experimenting with using SURF descriptors on a face extracted using OpenCV's Haar Cascade features, and this appears to get me closer to the intended result, however I am unable to think of a way to efficiently lookup and compare roughly 30 descriptors (which are either 64 or 128 dimensional vectors) in a database. I've done some reading about LSH and Spectral Hashing algorithms, however there are no implementations to be found for Java and my math isn't strong enough to implement them myself.

Does anyone have any thoughts or ideas on how this might be accomplished, or if it is even possible?

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Hashing isn't complicated, nor do you need a degree in maths.

Assuming that any 2 images will result in a fairly similar number of 'descriptors' then it only requires that you get a reasonable match with enough of them to get to a high enough confidence factor.

How specific these descriptors are determines what level of collision you can accept in your hashing algorithm.

As you have several of them, I would suggest that you don't need anything too sophisticated - after all, you probably want a level of 'fuzziness' in your search?

Start with something simple - experiment and refine. You might even find that you'll need different hashing for different descriptors - i.e. some might be more specific than others?

Hopefully some food for thought.