Algorithm Clones Facial Expressions And Pastes Them Onto Other Faces 31
KentuckyFC writes Various researchers have attempted to paste an expression from one face on to another but so far with mixed results. Problems arise because these algorithms measure the way a face distorts when it changes from a neutral expression to the one of interest. They then attempt to reproduce the same distortion on another face. That's fine if the two faces have similar features. But when the faces differ in structure, as most do, this kind of distortion looks unnatural. Now a Chinese team has solved the problem with an algorithm that divides a face into different regions for the mouth, eyes, nose, etc and measures the distortion in each area separately. It then distorts the target face in these specific regions while ensuring the overall proportions remain realistic. At the same time, it decides what muscle groups must have been used to create these distortions and calculates how this would change the topology of the target face with wrinkles, dimples and so on. It then adds the appropriate shadows to make the expression realistic. The result is a way to clone an expression and paste it onto another entirely different face. The algorithm opens the way to a new generation of communication techniques in which avatars can represent the expressions as well as the voices of humans. The film industry could also benefit from an easy way to paste the expressions of actors on to the cartoon characters they voice.
compression approach for video chats (Score:2, Insightful)
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You probably generate and transmit more procedural data versus a video stream, sorry to break it to you. You also introduce lag, which many of us don't like (and this would suck balls for those using sign language to communicate via video chat.)
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Looks like he's pinching a loaf. Xerox that look.
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Matrox HeadCast [zdnet.com] in 2001.
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Mathematical definition for (Score:2)
nice
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Mona Lisa (Score:1)
now anyone can see their Mona Lisa smile!
already there (Score:1)
Easy for the Chinese... (Score:1)
Easy for the Chinese researchers, since... Chinese Faces All Look Alike.
Bada-bum-tish.
Thank you, try the waitress, tip the salmon, something-something "all week".
(And for the humour-impaired, I certainly don't think "they all look alike", I live with a Hong Konger... Just playing with an old trope.)
Hollywood wants this! (Score:2)
Paging Keanu Reeves, Kristen Stewart...
"They said it was a break-through!" (Score:2)
The film industry could also benefit from an easy way to paste the expressions of actors on to the cartoon characters they voice.
The Adventures of Mr. Incredible (with Commentary) [youtube.com]
The animator of a feature film begins with a study of an actor's vocal performance, facial expression and mannerisms but the end product will be shaped his own imagination and interpretation of the character
One reason for Disney's recent string of hits is that the studio casts its nets widely and avoids using overly familiar celebrity voices in predictable ways.
3d animation already uses this technique. (Score:5, Interesting)
Another good technique is to sample FACS (Facial Action Coding System) style muscle activation data from the source head and just add the individual deformations together on the target head. The proportioning is already taken care of by the definition of the FACS shapes relative to each head.
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Also at 2:05 you can see the mucle set that was used to drive the deformations of the face.
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You don't have to use the dots, it just makes things easier to track. Check out http://facewaretech.com/ [facewaretech.com] , they do a pretty good job without the dots.
Seen before? (Score:2)
I believe I saw a demo of this technology back at Uncertainty '99 when Matthew Brand presented a paper titled "Patter discovery via entropy minimization" (TR-98-21 from MERL ("A Mitsubishi Electronics Research Laboratory")). The demo was a video of an infant who started to lecture the audience on the technique. I was quite impressed. I recently found a copy of the paper via google.
Look ma, no teeth? (Score:2)
None of the example pictures in the article and the paper @Arxiv show target/source person flashing a toothpaste smile. Does this mean their algorithm's only good for Mona Lisa? Maybe that's their secret (limitation)?
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The target person's smile looks completely computer-generated and not natural at all. They are very far from a toothpaste smile. Real actors in movies need not fear Hollywood replacing them with no-acting-talent pretty faces.
Emoji (Score:1)
:-)
Coming soon to GMOD? (Score:2)