Machine Learning Allows Actors To Create Games That Understand Body Language 30
ptresset writes "Goldsmiths college is developing technology with natural responses to human interaction. The technology enables video games characters to move in a more natural way, responding to the player's own body language rather than mathematical rules. The hypothesis is that the actors' artistic understanding of human behavior will bring an individuality, subtlety and nuance to the character that it would be difficult to create in hand-authored models."
Learned that first (Score:2)
Naturally
Question (Score:3, Interesting)
Re: (Score:2, Insightful)
What exactly makes this require machine learning as opposed to some other method?
Hey that's so weird, the submitter had the exact same thought you did! I know, right? Crazy world, man.
It's as though he anticipated this and included the last link in the summary for the sole purpose of answering this question. It's so amazing what you can learn when you take a few seconds to read what's in front of you instead of rushing to get an early post. Cosmic!
Re:Question (Score:4, Informative)
Two things :
1) Human learning isn't special. "Machine Learning" is a buzzword that sells clicks, or whatever metric TFA is after...
2) Humans already know what body language is natural. We might not know exactly how to express/quantify what is or isn't natural, but we sure as hell know it when we see it. Hence: uncanny valley. If we can program some basic keys and triggers into a computer system - have it learn "yeah... that's too much eye contact, you're creeping me out" - we can not only make more realistic games (i.e. by not having to hand-program every bit character in the back, but rather just have them mill about and follow the standard conventions of human interaction) but it would be a big step for real-world applications, and having our future droids not look like c3po.
2a) Seriously though, play a BioWare game. While most of their games are fun and contain varying levels of good/great writing ... the way characters voice and face sync up (or rather, don't) can be more than a bit unsettling.
Re: (Score:2, Insightful)
"Machine Learning" is a buzzword that sells clicks, or whatever metric TFA is after...
Machine learning is a branch of AI. It's as much a buzzword as geometry is (which, as you know, is a branch of Mathematics, not a buzzword, although it's true it's easier to sell a machine learning paper than a geometry one). Very basically, machine learning means feeding a lot of data to an algorithm, it learns from the data and can give good enough solutions for new problems.
Re: (Score:1)
Very basically, machine learning means feeding a lot of data to an algorithm, it learns from the data
No.
It means an algorithm which mutates based on the data inputs. What they're describing is very similar to what companies like Pixar have been doing with live-action motion capture applied to computer models. You rig up an actor with sensors and capture his motion, then apply those motions to the computer model instead of having somebody hand-animate the models.
What they're doing is slightly more along the lines of machine learning, but it's still a bit of a stretch to call it that. What they're doing is g
Re: (Score:2)
No. It means an algorithm which mutates based on the data inputs.
I thought it was a branch of computer scientific concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, This does not imply that the algorithm mutates, though that is one way of allowing the computer to evolve.
Re:Question (Score:5, Informative)
A non-machine learning method would entail specifying a set of reactions for the set of inputs. If A then B, and if C then D... the hardcoding the relationships between the inputs and outputs. Machine learning, on the other hand, involves the computer program going through a pile of data and determing the relationships between inputs and outputs.
This problem is probably well suited to the technique because there are so many possible inputs and many nuanced outputs. In that situation, it's difficult if not impoossible to construct a programatic flow-chart that will perform well.
There's tons of material on the web now to help teach about these methods, like Coursera.com's courses in AI, Machine Learning, and even Probabalistic Graphical Models..
Re: (Score:2)
Answer (Score:2, Informative)
It presumably requires machine learning because the inputs (all possible permutations of bodily motion) are so diverse that it becomes pretty much impossible to hand engineer a decent response to them. Therefore you feed some training data (motion capture of actors) of paradigmatic or common inputs and let the algorithm learn how to respond to the myriad other inputs that you haven't provided. The situation is exactly analogous to handwriting recognition algorithms that the post office uses to sort and rout
Re: (Score:2)
Re: (Score:1)
A better summary (Score:1)
So, to cut past this article not knowing how to write, this is what's happening: A set of motions are captured for two people, one correlated to the other. So X is correlated to Y. Then, when gesture X is exhibited by the player, animation Y is done by the in game character. This is just coupled by the age old branching tree structure for AI to get some silly interacting dancing man.
It's not really interesting, it's just: When player moves X choose to play mocapped animation Y(z) where z is random (or whate
I want a game that understands sarcasm (Score:1)
Now that that's a really useful invention....
Re: (Score:2)
I'm not sure what your thesis is, or who you are quoting, but whatever you're trying to do is sadly lacking in enough formatting to make it clear. Perhaps you could get some assistance from the APK jackasses in how to use the site.
Duck Hunt (Score:3)
Can we finally kill that stupid dog by flipping it off?
Pedantry (Score:2)
I've done a lot of machine learning. It's very much mathematical rules. The inferred rules just happen to be so complicated that it's often hard to recognize them as such.
Maybe the submitter meant "hand-crafted decision tree".
Re: (Score:2)
Re: (Score:1)
I understand the confusion. I believe context and choice of assumption is important in this situation.
The source article opens by indicating design/development is the area where advance has been made... "shows a new approach to designing video game characters that can respond to our body movements and body language." While they speak to "having to think about mathematical rules," there is no indication that such rule would be or are precluded from a mature model.
The innovation implies the challenge, "h
Wait a damn second!! (Score:2)
magic instead of math? (Score:2)
responding to the player's own body language rather than mathematical rules
I confess to not reading TFA, however, I have yet to see machine learning that doesn't rely on mathematical rules.