- Thank you for the introduction.
Okay, hello everyone, I am Baris Unver,
a fourth year Ph.D student in computer science
at the University of Minnesota.
I am working with professor Lana Yarosh
and studying Video-mediated Communication in HCI.
So, we did this study last year in Microsoft Research,
I was an intern, I did with John Tang, Gina Venolia
and Kori Inkgen, and my two colleague intern friends
helped me on the study, and so what if we have
a mobile phone and built in camera and internet access.
So, we live stream, as normal people, and can you
live stream without using your hands?
So, this was our motivation and question.
And there are some solutions out there.
Like, this.
Or maybe this.
And it's too early, if you've watched the Black Mirror.
And, our assumptions are, we have infrastructure
cameras everywhere, so if we can control them
and if we can get collect that all streams,
and create another interesting experience,
is it possible or not?
We tried to implement it.
So, the related work says people use live streaming
for communication, collaboration, sharing
the experience, personal branding and making money,
and just for fun, and there are lots of applications
that you can use for this purpose.
But, there are some limitations and problems.
Traditional systems face limitations,
one hand always occupied, y'know,
you have to look at screen, it's distracting,
demanding and bandwidth, latency, video quality,
battery, heat and other problems,
and also we were suffering from those problems as well.
And, so if we use infrastructure cameras,
we are solving most of these problems.
They always have wired internet access,
and they're plugged, so the problem is
how can we collaborate this in a rhythm.
So, our research questions, should remote viewers
have the autonomy to choose an independent screen?
And, in what ways would lack of shared
visual context be a problem, or disruptive or helpful?
How would the local users lack of awareness
affect our experience?
So, I'll be talking mostly about the user study side.
So, we built a system, we used some
web cameras and Raspberry Pi's.
We created some units, so if one unit
is consisting of two camera, a test camera
and a face camera, so we called this as a unit,
and we used five units and a wide angle lens
attached room camera.
So, here are the locations and positions
of the cameras, so here there's a wide angle
room camera, all we can get is direction.
And we had a table and we have five task spaces.
Which is, y'know, marked labeled with colors.
So this is the system architecture,
so all the cams goes to FF MPEG and then
it pushed the walls of it, a media server,
and then to the web browser, and it expands
to the viewers, and we tried to implement some
face tracking, but we were unsuccessful,
because of the light and the angle of the view,
so we implemented a physical force approach.
I'll tell you about it later.
So, how did we investigate?
We designed a user study, to explore our system.
So, we used three conditions, the first one
is the base, handheld mobile phone condition.
And the second and third ones are
hand-free models, one with manual condition
and the second one is the auto condition.
So, this is the room view.
We have some hotspots, if you click
this hotspots, you can switch to this
task view camera, any time, and here is
a view from task view, and a view
from face view camera.
So, you can use this, use interface
in hands free manual condition.
So, how did we measure, and what did we measure?
We recruited 54 people, and the average was
21 years old, and they were 18 groups of 3.
And the task was a collaborative memory game,
we used three different sets of pairs,
and fishes, butterflies and flowers.
So we welcomed in from the participants
and they practiced before studying,
and we assigned some users to local,
and some users to remote users, and they did
they completed post-game surveys and end-of-study
survey, and we did a semi-structured interview
at the end of all conditions.
So, these are the data we have collected.
So, the limitations, so it was a lab study,
so it's supposed to be a real-life study,
open space, but it is very difficult
to find such a space which full of cameras
and control that space, so we had to do a lab study.
But we are planning a study in a while.
So participants, they don't represent
the general public, because we recruited
all of the participants from Microsoft Research,
they were interns at that moment.
So, the first condition, handheld mobile
phone condition, I have some short videos.
So, we can watch them and see.
I think we can't hear.
Okay, so this is handheld condition.
So, you can see that it's this link.
We have to be attached to streamers view,
and the streamer is walking around
inside the lab and trying to find
the pairs on the cards and viewers
are trying to help the streamer.
This is the handheld condition again,
and from the view of viewer B.
The same thing, the hands free manual condition.
So we can see the viewer A on the left side,
and viewer B on the right side.
They have the same, they have different views
because it's a manual condition, so they can
see which, any camera as they want.
So it's giving us some sort of freedom.
And the auto condition.
Again, viewer A and B.
But only one view, they have no control on the views.
You can see how relaxed, so they don't
have to manage anything.
So for the hands free auto condition,
we used a visual force approach,
we trained a person and that person tried
to follow the streamer inside the room.
So let's switch to results and our discussions.
So after completing the three games sessions,
persons ranked the conditions by preference,
this is the, these charts belong to the streamers,
and streamers ranked the automatic condition
significantly higher than both manual,
and handheld condition.
And streamers also ranked in the preference,
also streamers ranked the automatic conditions
significantly higher than the handheld condition.
In able to communicate and best sense of room.
And these are belong to the viewers.
If we check the performance, there were no
significant difference between each condition,
and we noticed that there was a learning effect,
but we counter-balanced for each condition,
so it didn't affect our study.
The interviews, we got lots of insights
and we learned lots of from the interviews.
So I want to cite them.
Consistent with prior work, we see that
remote collaboration using a handheld setup
is cumbersome for the user streaming the video.
Participants supported that holding the phone up
for extended periods of time was tiresome,
and caused them to alter their experience.
Furthermore, streamers reported that it was
difficult to remember to adjust the view
appropriately while performing the task.
This often led to poor viewing angles
for the remote viewers.
From the viewers perspective,
the handheld condition was preferred the least.
Viewers reported that, due to the natural movements,
the handheld condition was less stable
and difficult to attend to.
Furthermore, viewers lost perspective of the room
and were limited to the field of view
provided by the streamer.
However, an advantage of the handheld condition
was that it provided everyone with a shared view.
Streamers reported that knowing what the viewers
were looking was helpful for coordination and communication.
And for the hands free conditions,
in the automatic condition, streamers were
informed that the view point
would be selected to follow them.
Streamers reported that knowing that
the viewers were following them made them feel
like the viewers were with them at all times.
Which made it easier to communicate.
In the manual condition, streamers had
limited awareness of what the viewers were attending to.
The opportunity for viewers to select alternative views
left the streamers confused about what
the remote user was looking at.
And they often claimed that they had to
use more effort to communicate.
However, some groups used the ability to look at
multiple places at once, to widen the work and multitask.
The viewers equal preference for the manual
and the automatic conditions.
They expressed benefits to each of them.
One participant made the following comparison,
I liked it very well.
I think it's summarizing.
We saw this kind of comparison with most groups.
Many viewers who preferred automatic condition
felt that it was easier to attend to and required less work.
In contrast, viewers who preferred the manual condition
enjoyed the freedom to navigate the room
independent of the streamer,
and the opportunity to multitask.
Furthermore, all viewers reported that the manual
condition gave them a better sense of the room.
So we also analyzed the videos.
Users had three separate views from the left
space and switched among them during the task.
Viewers used the task view most,
followed by the room view.
We also provided face view, but with limited
use of the face camera, likely due to the
structure of the task.
Participants reported some explanatory
use of the face camera but they claimed it was not useful.
In addition to the recording viewer actions
during the manual mode, we also simulated
the automatic condition for a comparative baseline.
We compared the differences between the two viewers
in a session and between the viewers and the WOZ
condition in session by measuring the amount
of the time they spent in the same view.
The results show that there is a significant
amount of diversity between remote viewers,
and also between viewers and the WOZ.
In the manual condition, we found that different
groups used different strategies to complete
the task, for example, some groups used
the manual condition to support multitasking,
while having the remote viewers look at
different task spaces than the streamer.
Viewers were also able to navigate to
the upcoming task space before the streamer.
In this work, we investigated opportunities
for hands free remote collaboration
over video systems, compared to traditional method.
We see that hands free condition is just
as effective as the handheld condition.
Here is a summary of our findings and comparisons.
However, results this work we will that
design of viewing experiences for hands free
video conferencing still needs further investigations.
So for the future directions.
So we found that both automated and manual,
manual and hands free automated conditions
they have their pros and cons, so we,
imagine a semi-automatic system,
to combine benefits of both systems.
And, we are planning a real life study.
Real, outdoor place.
So, here are the takeaways, hands free
multi-camera system to support
sharing experiences over video.
Our study found a hands free condition was just
effect as the handheld condition.
Both streamers and viewers preferred the
hands free remote collaboration system.
Despite it's limitations.
Furthermore, the automatic hands free
condition provided more contacts between
the streamers and viewers, which
contributed to more seamless communication.
Thank you.
(audience applause)
- [Host] Thank you, Baris.
So, are there questions?
And while you are thinking about,
I start with a question.
- Sure.
- [Host] I did not, to be honest,
I did not quite understand the rational
behind this, so what kind of applications
are you really looking at?
I mean, typically, you don't play
collaborative memory games, but at which point
would it be useful to use such a system?
Maybe you can clarify this a little bit more.
- Yeah, sure, thank you.
So imagine you are in Disneyland, or a controlled space.
You are having fun but you have to use
your mobile phone and to share your experience
with your friends an family, they are not with you
at the space, so this is limiting your
experience, so how can you get rid of using this?
So okay, this is a controlled space,
we have the control of all cameras,
we can get all the streams, and we can track you,
we know your face, we can track you and we can
narrate the scene, instead of you.
Yeah, this is a kind of example scenario.
- [Host] Yes, but of course, this would need
a lot of equipment in a room, so I did
not really get the link between your motivation
which actually says, if we have video surveillance
everywhere, we could just use it for such purposes,
so this is my take on it
- Yeah, okay.
- [Host] So, maybe I'm wrong, so I don't
understand because in particular, since I
as a particular user have no chance to get
all the video information from all the cameras,
which might be from different purposes like this,
the police, pardon, this is private, pardon,
this is a Disney part of the camera,
so the system, so how do we use it,
how do you, what's your idea on that?
- Maybe we will see in the future,
y'know it's not too easy to talk about it, I guess.
Too early, yeah.
- [Host] No, it's never too early to talk about
privacy, never.
(laughs)
- Yeah, for privacy, I mean
- [Host] You should talk about it as early as possible.
- If you're okay, if you accept that you're filming,
y'know they're filming you in that space, that's okay.
But I am sharing the privacy concerns with you.
- [Host] How do you accept all the other viewers,
the remote viewers, how do they access
all the surveillance cameras?
- Well, you have to provide a system.
So, that's what we did, we have to provide a system,
that we are assuming we have the access.
Yeah.
- [Host] Good, are there more questions?
Beside my critical questions?
Alright, so if not, so let's thank all our speakers again.
(audience applause)
- Thank you.