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This seems to indicate that the authentication system is using a binary comparison "is this face the same as that face" for each stored face. But why would it n
by ajb 5y ago
This seems to indicate that the authentication system is using a binary comparison "is this face the same as that face" for each stored face. But why would it not do instead "which is the nearest face to this"? Surely you can't find one face which is the nearest to 40% of the DB? (unless this is yet another counterintuitive feature of high-dimensional geometry)
- hansvm 5y ago> unless this is yet another counterintuitive feature of high-dimensional geometry As it turns out, that _is_ another feature of high-dimensional geometry. The details depend on how many dimensions your images have, the similarity metric being used, how big your database, is, .... For a brief illustration, consider standard euclidean space. If your images have D dimensions, ignoring some pathological cases you can find a point equidistant from D+1 of them (and if you have more dimensions to work with you have a lot of points to choose from). If D+1 < (40% of database) then you've accomplished your goal. Note: It is possible for such a point to be arbitrarily far from the rest of your database (in context, that it would look nothing like a face). Spare dimensions can give you enough freedom to place it "in the middle" of your database in some sense, not just some point in the middle of nowhere that's an equally bad match for everything.