- Thank you.
And good morning to you all.
It's nice to see that there are so many of you here.
So my name is Teija Vainio.
I come from Finland from the city called Tampere.
As Ella mentioned my presentation is about urban planning,
how to support citizen participation
in urban planning processes,
and how to use eye tracking technology.
For urban planners, architectures, designers to understand
and communicate with citizens about what is
attractive environment from
a non professional designers perspective.
And this is a case study,
this case study is part of the contour project
conducted at the University of Tampere,
or Tampere University, but we use both names nowadays.
The project were funding by the Academy of Finland.
My co-authors here are Ilari Karppi, Ari Jokinen,
and Helena Leino.
All them are from the University
of Tampere or Tampere University, and
Ari and Helena, they background in environmental policy,
and Ilari's background is administrative sciences,
and my own background is in
computer science and architecture.
So our background somehow describes our views
and perspectives into this phenomena,
how to use technology
in urban planning processes.
So I mentioned this case study is about urban planning
and filling the communicative gap between
professional planners and non professional planners.
Particularly when professional planners are
using visual representation of the,
of the future urban areas.
And they are aiming to answer several questions.
Our research question in this case study was
what are the strengths and challenges when applying
particular technology, in this case eye tracking technology,
to gain insights on human attention
with planning illustrations and photographs that architects
and designers are using of urban environments.
So we had experiments
in two Finnish cities,
in Espoo and Tampere, we have around 30 participants,
and there were both professional and
non professional urban planners.
And what we got as an outcome is this type of results.
So this is a heat map, describing after one second,
what the participant is looking at.
And this after one second is very interesting outcome
because it's unconscious reaction
or action actually.
Then we see what is the most interesting,
or what is the first thing actually,
what caught the attention in particular
illustration or photograph or design.
And this is after five seconds in the same place.
But as you can see,
this heat map describes
where the participant is looking at,
but this doesn't actually tells us why.
And that's very important to understand for designers.
What we learned during this case study is that
what people find attractive in urban environments
is very context sensitive and subjective matter.
For example,
if the participant is very familiar
with the places before hand,
or if the area that designers are
planning is
unknown to the participant,
it have an effect to how he or she reacts.
And by analyzing what physical elements
people look at in different environments
we could understand what catch their attention,
but we can better understand the elements
of urban design quality.
And this is very important to the designers,
and architects and, urban planners in general.
To understand what is most interesting or what
is catching the attention in urban space
when the general aim is improving the design quality.
And what else we find that this type of technology
provides tools for this type of purpose
to bring new knowledge and understanding
to improve the design quality and understand
why people are interested in particular elements
in urban environments.
This is another place
in Tampere City.
As you can see the results are like this heat maps,
but what the researchers and designers have to do
before they get these types of results,
is they have to define areas of interest.
If they are using eye tracking technology,
it's important, and this is one of our key issues
or lessons that we learned,
that when we are defining
areas of interest,
that has an impact how the
results are analyzed.
And this is one example how we analyze or define the areas,
and this is another one.
So what are our implications for practice
based on our case study?
It's very important to design areas of interest
so that they support your questions and hypotheses.
And above all you have to define the goal for measurement.
Are you interested security,
safe traffic,
or attractive environments, green places, things like that.
And you must also define if the goal of the element
in urban environment is to be attractive or not.
This means that for example,
if you have street view or street area
and there are traffic lights,
trees,
open spaces,
and things like that.
And then one
thing is also that you have to compare areas of interest.
This means that as I show you
there are several areas of interest
and if you compare them
then you might get
information or knowledge.
For example is the lightning
or the green spaces
attractive enough or something like that.
And most of all I think this is the most important
outcome of our case study that you have to analyze the
quantity of results with the participants.
As you may know that when you are using this type
of technology you have plenty of quantitative data.
And you can analyze that with statistic
and things like that, but to understand why
people are looking at something, it's very important,
and eye tracking probably won't tell you that.
For example when we were
doing our case study
one of our participants look at
particular door in a street view
and we were wondering why that door in a building
is so important for her.
And then she explained later on in a workshop when
we were analyzing these results with the participants,
she told us that her children were
taken care of in that building,
it's a daycare center for children.
And there were some problems with
that center in a couple of months
and she was wondering
if it's still open or not.
And then we realized that okay,
this is very personal thing for her
and that's why she was looking
at that particular target so long,
but what it tells to urban planners?
Well, design doors or not,
but I think, and we argue that
this type of example gives you the idea
that if you are just looking the quantitative data,
it doesn't give you the whole picture.
You have to interpret the results with the participants.
Yes, I think I leave my presentation here
and thank you for your patience
and I'm anxious to hear your questions.
Thank you.
(audience applauds)
- [Woman] It's more of a clarification,
thank you, thank Teija for the very nice presentation.
I'm just curious about your thesis,
so did you, were the participants,
tested eye tracked in solo mode?
So were they alone, when they were looking at space
or were they doing it in conjunction with someone else?
- They were solo testing the, yeah.
Yes, how do you think that it
will change the results or outcomes?
- [Woman] Yeah I was wondering that if for example,
you are, let's say I'm with someone
else, like we're in groups,
and you are observing something, it's like you think
very much the social aspect,
someone who I mean, immediately when we are in the group,
you are skewed, that you are communicating somehow,
and it might influence the way you are looking at things,
because when you are with someone else,
and especially when there is a discussion,
that same trigger by wonderment,
or by anxiety, or by a bridge.
I remember back when the you know like the ones outside
in the city, that may trigger another layer
of let's say direction on what you are looking
when you are with someone else
`as opposed to when you are solo.
So that's why, it's very much a social behavior,
as opposed to...
- Yeah-- - [Man] Sorry to interrupt,
do you wanna come back here, let Lindsey set his laptop up?
- Oh sorry yeah.
- [Man] And then you can attempt to hold your conversation.
- [Woman] (laughs) So, yeah.
That's why I was asking, I was
just curious of whether that is something...
(man mumbling)
- Yeah that's true.
Maybe, yeah.
I was talking more about focusing on understanding
how to interpret
what is attractive
in a visual representation.
But maybe we can view that space by what
experiments set up in the future,
because I'm quite sure that we would
be very interesting to see
how the social aspects are affecting that part.
In this case like we were focusing on only psycological.
- [Man] You have a question?
- [Audience member] I do because
I know that in architecture I study,
I was hoping for urban planning,
there was a discussion around what it means to use
2D renderings, and how kind of it spreads them around,
this the architect dealing with urban environments or not.
So I was wondering if you also want to use this
eye-catching technology, for example, for 3D simulation,
then how you think that might change the results
of the demonstration?
Yes.
That's a
good question, because I know that in my home land,
in Tampere, they are building a tram there currently
and they want to use three-dimensional
visualization because they are building
the tram now, so they have all the
visualization and three-dimensional
models, how it can be look at in the future.
And they are used to, to use this kind of technology
and we agree that it's a good idea,
but for now we have views that they
have some plans to do that on.
- [Man] One more question within 10 minutes?
Please.
- [Woman] So I also come from eye-catching field,
so I'm sort of wondering, because it's normal that
sunlight is quite a problem for the potential
thing that would affect the accuracy
of the eye-catching system.
So have you ever considered
like for example, on all your participants
doing experiments in the daytime
or by all in the same locations
do same light composition?
- [Vainio] Ah yeah, that's true too.
No we use the same
data and
conditions were the same.
Attached to that, when we are checking
for example the lightning, or have some noise,
maybe, on something like depots,
definitely attached, or
probably, I'd say attached to the results
we haven't found that yet, though.
That's a future we hope for.
We still have the time for question,
can we, anybody else?
Anyone? (clears throat)
(man speaks away from microphone)