[MUSIC]. 
In the previous lectures, we've been 
discussing data and visual mappings. 
Now we're going to talk about the other 
end of the pipe line. 
How that information is processed by 
human brain. 
This is the first of three lectures on 
visual perception. 
70% of our body's sense receptors reside 
in our eyes. 
Our very language resonates with the 
importance of our eyes. 
Metaphors to describe understanding often 
refer to vision. 
I see, insight or illumination. 
Colin Ware stated in 2004. 
They eye and the visual cortex of the 
brain form a massively parallel processor 
that provides the highest bandwidth 
channel into human cognitive centers. 
In these three lectures we're going to 
describe how it's important to understand 
how visual perception works in order to 
effectively design visualization. 
The first key principle to keep in mind 
is that the eye is not a camera. 
A better metaphor for vision was given by 
Christopher Healey in 1995. 
It's a dynamic and on going construction 
project. 
It's important to keep this in mind as 
you go thru the next three lectures. 
Because when you go design a 
visualization, if you think of the eye as 
a camera, it can lead you to some eno, 
erroneous conclusions. 
Attention is selective. 
We, we all know that. 
it's filtered to a high degree. 
And it's really cognitive processes that 
transform the visual information into 
something that we can comprehend. 
The field of psychophysics is concerned 
with establishing quantitative 
relationships between physical 
stimulation and perceptual events. 
So we're going to be talking about some 
of the important discoveries made in this 
field in the next three lectures. 
Let's think a little bit about how to use 
perceptual properties. 
Information visualization should cause 
what is meaningful to stand out. 
So what do you see in this image. 
Can you see the 2 spots that differ from 
their surroundings? 
Why do you see them? 
We're going to answer that question in 
the next few slides and lectures. 
Some important differences between eyes 
and cameras. 
Cameras have very good optics. 
They have a single focus, they maintain a 
white balance and a single exposure. 
And they also do what's known as a full 
image capture. 
In another words, all the photons coming 
into the eye are captured with equal 
importance and at the same time. 
The eyes on the other hand have 
relatively poor optics. 
They're constantly scanning. 
This is known as saccades, the shifting 
of your eyes to various positions There 
constantly adjusting focus, there 
constantly adapting, both the white 
balance and the exposure. 
What's really going on is mental 
reconstruction of the image, sort of, as 
we'll find out it's not even a complete 
image thats reconstructed. 
So here's one example. 
Visual perception really isn't just 
camera work. 
Looking at this checker board it's pretty 
clear that square A is darker than square 
B, right? 
Turns out if you gray out the image, you 
see the truth. 
Square A and square B have identical 
pixel values. 
As a matter of fact when I first saw this 
image I didn't believe it. 
I actually put the image in Photoshop and 
used the Eyedropper tool in order to find 
out what the RGB values were of those two 
squares. 
And yes indeed they are identical. 
So you're welcome to do the same you can 
take a screen capture and test it out 
yourself. 
But it's pretty interesting. 
The human visual system is so dependent 
on context and upon reconstructing the 
image that we see these two squares, 
which are identical as quite different. 
Color is relative as are many other of 
our perceptions. 
If you look at this slide, doesn't it 
look like the x on the left hand side is 
gray and the one on the right hand side 
is yellow? 
But if you go look at were they connect 
at the center bottom of the slide you'll 
see that they're identical. 
And that's again because the eye 
perceives differences. 
It does not perceive actual pixel values. 
So in conclusion I hope you've taken away 
from this lecture that the eye is not a 
camera. 
In the next 2 lectures, we're going to 
discuss more about how understanding how 
the visual perception can help us develop 
more effective visualizations