By zooming in on high-resolution passport-style photographs, Jenkins and co-researcher Christie Kerr of the School of Psychology, University of Glasgow were able to recover bystander images that could be identified accurately by observers, despite their low resolution.
To establish whether these bystanders could be identified from the reflection images, the researchers presented them as stimuli in a face-matching task. Observers who were unfamiliar with the bystanders' faces performed at 71 per cent accuracy, while participants who were familiar with the faces performed at 84 per cent accuracy. In a test of spontaneous recognition, observers could reliably name a familiar face from an eye reflection image.
Coming soon to Picasa, we can only hope.
Of course, this requires absurdly high-resolution images without the slightest camera shake. See also: http://www.cs.columbia.edu/CAVE/projects/world_eye/
Makes me want to go shopping for reflective objects on ebay and see what I find.
You want to see that many naked strangers?
Only on teakettles.
Yep, tea kettle guy was way ahead on this...
Could you turn off the hotlinking image for theoldreader.com as the referrer? It's an RSS reader.
Been opening up and refreshing the pages ever since the death of Google reader. A hairy ball in a cup is a funny thing, but it gets old pretty quick.
Just to add my info, for whatever reason I don't have this problem (i.e. the pictures and videos show up for me). Linux/Chrome/AdBlockPlus and I use "list mode" in theoldreader.
More amusingly The Old Reader seems to mix up the preview images for youtube videos for me. What was supposed to be a video of the aurora borealis showed up as the GAGABOT.
I won't believe I'm living in the future until they find a way to do it with CCTV images.
This attempt to approximate Voroni tessellation on a grid explains why information is destroyed by both analog and digital information processing equipment. Fight back with error correcting codes today. Available in combinatorial-explosion moral and painstakingly time-wasting steganographic binary.