Video

Transcript

hi everyone I’m Hannah calling in from

New York so I did my project not

generating emotional landscapes and the

background on this is that I’ve been

pretty interested in just an emotional

datasets for most of the past year and

earlier in the year I created a emotion

tag to landscape dataset where basically

I took seven different classes of

landscapes and used gram flour to have

people tag them with eight different

emotions and so some of the results I

got from this included these aren’t some

emotion tagged fields so you can see

that there’s a pretty greater

distinction between emotions here some

disgust images mostly browns and greens

a lot of water

swampy Lake kind of things fear was like

both obvious forests kind of dark blue

nice area tech things but also like

conceptual fear of the open ocean and

surprise had a lot of like bright colors

and things like that so I wanted to take

this data set and see if I could

actually generate emotional landscapes

from it so first I tried again but that

was very quickly unstable as you can see

here and so I ended up trying a multi

scale additional BAE which is based on

Emily Denton’s 2015 paper and so I’ll

show you some of these outputs these are

64 by 64 pixels generations so each of

ocean row has the same defect there as

the input so here’s one set then I’ll

just go through them

so here’s anger anticipation disgust

which you can see has a lot of grounds

and greens fears pretty dark and gloomy

Joy’s a little brighter sadness is

pretty muted

surprise has some surprising colors I

guess trust is very bright and calm

here’s another set

and then I also tried doing landscape

specific generations so here are 32 by

32 generated mountains slightly blurrier

but I think the emotions still hold

and then forests

and that’s my project great does anyone

have any questions to directors now so

the question was if people will agree to

the emotions of the generated samples

sorry do people agree on the generate

examples if you show them a generated

sample survey saying disgust or fear

I think definitely if I show them like

ten in a row oh it like like like these

kind of things where there’s a sample of

ten then they do there are some

individual ones that don’t totally feel

right but as a whole they do I think

like fear versus joy that looks pretty

right to me any other questions

I’m just going to bring hi so other than

color colors were there other aspects of

pictures that would correlate with

emotions like symmetry of the image or

certain shapes that appear in the image

I actually noticed that anticipation had

a lot of contrast more than I think more

than most of the other ones someone said

that maybe that was like a lens flare

effect or something so definitely like

shadows and and contrast between lighter

and darker areas was another thing I had

noticed but for the most part it did

seem to be colors although with with the

mountains also the sky light seemed

different

so like fear the mountains all seem to

be slightly higher than some of the

other emotions which maybe makes sense

if you’re like looking up at a mountain

versus like looking down from a mountain

or something like that

hey we’ve got another question when you

were building the data set with

CrowdFlower did you only select for

English speakers or did you to translate

those 10 emotions to different languages

no I only I only selected for English

speakers it’s actually part of a bigger

project I want to do which is like

seeing if like people in different areas

type things differently like if people

who live near mountains type mountains

differently and things like that

so I got started in the US and like in

you in people who I put in there US

cities so I could like start

investigating that