A single picture is surprisingly effective in recognizing that person in another photo. I've been playing around with a python wrapper on dlib's facial recognition [0] and it's astonishing how it can identify people from just one photo. It's not like other machine learning methods that include training a classifier or even fine tuning a classifier. It works by encoding the persons face to a 128 dimension vector and then using that for comparison.
The accuracy from most methods is between 99.2% - 99.8%, but the problem is that the training samples are too easy and controlled. It's sensitive to lighting. Google's most recent paper [1] on Facenet found 99.63% on the easy Labeled Faces in the Wild (LFW) dataset, and an impressive 95.12% on the Youtube faces dataset, presumably a much more difficult dataset.