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 Features
Not
Just Another Scary Face
You
ever notice how all the young people on Murder, She Wrote looked
alike?
I'm serious. Every episode, Jessica Fletcher would be visiting a friend
somewhere, somebody would get murdered, and there would be five or
six suspects. The older people were usually played by character actors
who've been around forever. But the younger people were all played
by canonically-attractive unknowns. Episode after episode, week after
week, there was an endless stream of blandly good-looking men and
women. If they didn't have different colored hair, I couldn't tell
them apart.
Weird, huh? I asked a friend in showbiz why this was so, and he said
it was because Los Angeles has a vast pool of attractive young people
all trying to get into television or films. The market's saturated,
so they're cheap -- if you don't care too much about acting ability.
On the other hand, try looking around at people's faces the next time
you go to the mall, or to work. The variation in human appearance
is enormous. Try to ignore the hair (whose appearance is at least
as much a matter of personal choice as it is of genetics) and concentrate
on facial features: eyes, noses, lips, chins, cheekbones. Look at
skin colors and textures. Hollywood does a very poor job of duplicating
the diversity of the real world on TV.
Of course, we're not in any position to throw stones. In the video
game industry, we've been turning out characters that look alike for
years. And not just somewhat alike -- exactly alike. Completely identical.
Game after game, level after level, we sell an endless stream of canonically
mean-looking bad guys.
The reason for that is hardware limitations, of course. You've only
got so much room in memory for sprites. You have to strike a balance
between diversity of characters and number of animation frames per
sprite. As a result, all Level 5 Bog Monsters look and act identically.
We're so used to it that we never question it -- it's part of the
landscape of computer gaming. But imagine a person completely new
to computer games encountering this for the first time: "Why is that
guy back? I killed him five seconds ago!" "No, it's a different guy."
"Then why does he look exactly like the guy I just killed?"
Well, I say it's time to put a stop to it. There's no longer any excuse
for it. We now have the capacity to make every single character in
a computer game a unique individual. They can not only look differently,
they can behave differently as well. How? With physical anthropology.
Physical anthropology is the study of human physical variation. Unlike
medicine, which seeks to learn about things that we all have in common
(so that we can develop treatments that work for everybody), physical
anthropology is the study of how we differ from one another, both
today and in the past.
There's a subdiscipline of physical anthropology called forensic anthropology,
which appeared prominently in the book (and movie) Gorky Park.
The hero, a policeman, has three bodies he can't identify. The faces
and fingers have been removed. He takes the heads to a forensic anthropologist,
who, knowing the average tissue thickness at different points on the
skull, is able to build up faces on each of the heads with clay. Ta-da!
From the shape of the underlying skull, the face is revealed.
There's actually a lot of debate about the validity this technique
in anthropological circles. For one thing, you don't know that a given
person's skin was of "average" thickness. For another, there
are aspects of our appearance that aren't governed by the underlying
bone: the shape of the ears, for example. The technique is useful
to get an impression of what the "average" Neanderthal looked like,
but it doesn't really matter if we get it wrong. It's another thing
to claim it's accurate beyond a reasonable doubt in a murder trial.
We don't have to live up to courtroom standards, thank goodness. But
I think we should start to apply the principles of physical anthropology
in our games. Now that we've got polygon people to work with, we can
create variation in each individual, by adjusting the positions of
the vertices that define a character's skin surface. I'm not actually
suggesting that you try to build up a face from the skull, like a
forensic anthropologist. Rather, I'm suggesting that you try to define
a set of adjustments to your "standard" polygon model which will enable
you to create individual people. For each vertex, you can establish
a formula that governs how much its position varies from the "average"
or starting case. You can't treat each vertex independently, however;
you will have to group them into meaningful categories and adjust
them collectively. For example, if a person has a wide skull, he must
necessarily have a wide jaw to go with it. You will need to examine
your model to create a hierarchy of vertices, so that the positions
of the major ones influence the positions of the minor ones. Motion
capture data uses a similar concept for the skeleton: the position
of the hand is dependent on the position of the forearm, which is
dependent on the position of the upper arm. Likewise, unless you're
creating a race of monsters (and I'm sure many of you are), you'll
want to preserve the bilateral symmetry of the human form: most people's
left arm is the same length as their right, and so on.
At this point some of you programmers may have switched off, thinking
I'm talking to the artists. I'm not. I'm talking to the programmers.
I don't think you should do this ahead of time, in a pre-rendering
production step. If you do that, you're just back to the old situation
of having a number of characters whose appearance is fixed. I think
you should do it on the fly, as the game is being played when
the character is "born" in your game. One pleasant consequence of
this is improved replayability -- the characters don't look the same
every time you play the game.
However, be warned: if you create individuals whose physical variation
is more than cosmetic -- if you start modifying their heights, for
example -- then you run into some tricky issues, because of the interlocking
relationships between appearance and motion. Suppose you decide you
want a character who is taller than the average, and you make appropriate
modifications to the model's leg length. As a result, your motion-capture
data is going to require some on-the-fly modification also. Since
your motion-capture data is (presumably) designed to work with your
"average" person, you are going to need to adjust it for each individual
to account for all the ways that that individual diverges from the
norm. In this case, the model's stride is going to get longer. But
once the model's stride is longer, you will need to modify the character's
speed and acceleration accordingly as well -- otherwise you'll get
the well-known "skating" phenomenon, where a character's leg movements
don't correspond to her motion across the floor. Getting this right
with fixed characters, with testing and tuning, is hard enough. Getting
it right algorithmically for all possible cases is going to be very
tricky indeed -- but I have faith in you; nobody becomes a game programmer
who doesn't already think he or she is a stone genius, right?
These adjustments can apply to behavioral characteristics as well
as cosmetic ones. Recently I was playing a game with a large number
of characters of different races. The designers had, rather interestingly,
given each character his or her own name, so they were uniquely identifiable.
However, all the characters of a given race and experience level had
identical abilities. In other words, although each Level 5 Bog Monster
had its own name, they all were exactly the same strength. Why should
that be? It would add interest and variety to the game for them all
to be slightly different, although clustering about a common average.
To set the strength of each Level 5 Bog Monster, the program could
have taken a starting value (the average strength of all Level 5 Bog
Monsters) and added a random number, positive or negative, to it to
create a unique individual.
If you do change a character's appearance, you should change his behavior
as well. Since we're used to an endless stream of identical bad guys,
experienced gamers will expect bad guys that look different to have
different skill levels.
Now your ordinary random number generator, if it's a decent one, is
going to return values which are uniformly distributed. If you use
it to create the variations from the "average" individual, then the
probability of ending up with an "extreme" individual is the same
as the probability of ending up with a "normal-looking" one. Unless
you're working on a game involving post-nuclear mutants, you probably
don't want this. Instead, you want small deviations from the norm
to be common, and large deviations to be rare. In other words, you
want the distribution of your random numbers to be governed by the
famous "bell-shaped," "normal," or "Gaussian" curve (they're all names
for the same thing).
So how do you generate random numbers with a bell-shaped distribution
instead of a uniform distribution? There are several ways to do it,
as with most software solutions:
The first way will be familiar to those of you who have played Dungeons
and Dragons. In D& D, to get the starting attributes of your character,
you throw three six-sided dice and add them together. When you add
uniformly-distributed values together, the probability distribution
of the resulting sums is, in fact, a Gaussian curve. The more values
you add together (the more dice you throw), the more accurately the
distribution resembles the "standard" bell-shaped curve. (In D&
D, you actually throw four dice and ignore the lowest one. This shifts
the average result to a slightly higher value, but doesn't affect
the shape of the curve.) If your random number generator is fast,
you should probably add about ten uniformly-distributed random numbers
together to get each Gaussianly-distributed random number. Remember
that you'll have to normalize the result afterwards: if you add ten
uniformly distributed random numbers between 0 and 1, you'll end up
with Gaussianly-distributed random numbers between 0 and 10, with
a mean value of 5.
Another way to do it is with a simple lookup table. Create a table
of, say, 100 integers, then fill it with numbers in a Gaussian distribution:
10 zeros, 9 ones, 9 negative ones, 8 twos, 8 negative twos, 7 threes,
7 negative threes, and so on down to 1 nine and 1 negative nine. Whenever
you need a Gaussianly-distributed random number between -9 and 9,
choose one of the table values at random and use it. (This example
isn't literally bell-shaped; it's shaped like a triangle, but it may
be close enough for your application. You can use a larger table for
a more precise approximation. Microsoft Excel has a function which
generates Gaussianly-distributed random numbers if you need to know
what to put in the table). This method means you only have to call
the random number generator once.
Finally, there's one more method which I include for the sake of completeness,
although I don't recommend it. You can compute the equation:
BELLRAND = SQRT(-2 * LN(RAND())) * COS(2 * PI * RAND())
BELLRAND will be a Gaussianly-distributed floating point value. The
mean value will be zero and the standard deviation will be 1. It assumes
that RAND() is a function which returns a uniformly-distributed random
floating-point value between 0 and 1. However, it's very slow. Any
formula that calls the square root, natural log, and cosine functions
probably has no business being in a computer game. And one other warning
about this equation: unlike the additive or lookup methods above,
this method has no upper or lower bound. In extremely rare
cases, it will return an extremely large negative or positive number.
You may need to set artificial limits on the result it returns.
In my previous article I argued against encouraging human diversity
in on-line environments, because I don't think on-line environments
are ready for it. Here I AM arguing for diversity in our artificial
characters -- because, with the advent of polygon people, I think
we ARE ready for it. We're on the threshold of a whole new generation
of visually fascinating computer games. If anyone has already done
this, or is contemplating doing it, please let me know!
-----
Ernest Adams is an audio/video producer for Electronic Arts, currently
working on the Madden NFL Football product line. Once upon a time,
he was a software engineer. He has developed on-line games, computer
games, and console games for everything from the IBM 360 mainframe
to the Nintendo Ultra 64. He was a founder of the Computer Game Developers'
Association, and is a frequent lecturer at the Computer Game Developers'
Conference and anyplace else that people will listen to him. Ernest
would be happy to receive E-mail about his columns at eadams@ea.com.
The views in his column are not necessarily those of Electronic
Arts. |
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