This paper is titled, spatial
augmented reality, visibility and line-of-sight
cues for building design, and the authors are James Walsh,
James Baumeister and Bruce Thomas.
And we are from the Australian Research Center
for interactive and virtual environments
At the University of South Australia.
CADwalk is a commercial system that provides
life-size, 1:1
scale, CAD visualization. Effectively
it's an empty Warehouse
with multiple floor facing projectors
where and uses can bring in and visualize their plans
at life size.
One of the issues for this is whilst we can visualize the plans
at 1 to 1 scale.
We can't easily show objects'
heights on the floor. To alleviate this
the system
has a large-scale
wall display to show a
perspective correct 3D rendering of the space.
Depending on the application
domain visibility for the plan
can actually mean life or death.
If we are designing critical confirms or military spaces,
if we don't have appropriate line of sight
in the space,
you could actually result in someone's death
or injury.
The problem that we are looking at for this work
was given
the flow projection is separate from the 3D
wall display,
how can we support query such as is location
A visible from location B.
And more fundamentally,
how can we easily communicate lines of sight
in this space
for both
novice and expert
uses alike,
because when design reviews are conducted
within a CADwalk space
that has end-uses from across the Spectrum
from CEO
all the way down to the people that will be
utilizing the space.
In relate work, spatial
augmented reality has been shown
have different constraints
versus head-mounted display,
all handheld AR
which is what people traditionally, think about what
we discuss
augmented reality,
and SAR's been used in collaborative scenarios before
including previously in building design
and planning.
Is also been shown
that it can cognitive load for certain tasks.
Irlitti et al explored
displaying users' relative position with spatial cues
in extended reality
using these projectors
and previous work in tablet based
building layout collaboration,
has found the even casual
users engage in more than just positioning objects
within the building.
What we need to be aware of
though is that
the special cues, whilst they have been explored
and prior work, whilst they communicate
an object's
relative direction,
this is not the same as communicating an object's
visibility and line of sight.
They are two separate things.
We developed a number of different visual cues
that we evaluated as part of our work,
but they needed to fulfill
three main requirements. They needed to work
within the existing CADwalk system.
Needed to support a range of use, cases and scenarios,
for example,
critical control rooms
military, and domestic applications. And again,
they need to be intuitive for both novice
and expert uses in the system.
We explored two approaches.
One was a quantified cue
that was used object within the space
and we refer to this as a fuel indicator.
The other cue is a continuous cue across
all objects in the scene, that we refer to
as a Edge Highlighting
The fuel indicator allows users to select an object
using a handheld controller, an eight segment
fuel bar then appears at that user's feet,
indicating how visible the selected object is from
the current viewport
As the user moves around the scene
you can see that the bar
either the fills up or becomes empty to indicate
the object's
visibility. An arrow
marker is placed in the outline of the selected object
and faces the user
as they move around the space to indicate that
that is the object that is selected
and it is facing back
towards the user.
The application for this will be explained
in a couple of slides time.
The second cue was Edge
highlighting and effectively what we had for
this was a virtual torch shining from the user's
handheld controller,
this then highlights,
all the edges of the objects in the floor,
that are visible from that controller's
location and view frustum.
Originally we had this attached to the
user's head, so that wherever they were looking,
they could be able to see the edge
highlighting for what was visible from that
current location.
However we found this was very distracting for users
and quite often
people would be looking a separate direction
to potentially, where they're wanting
the cue to actually appear so we slaved it
to the user's hand
controller, rather than the user themselves.
The other thing that we were interested in exploring
was this idea of having an inside-out
versus an outside-in
view
Traditionally in the space,
if we looking at whether a supervisor, in this figure
X, can see
their subordinates,
a, b, c, and d, we can offer this as an inside-out view.
But what about if we invite this approach
and we have an outside-in view?
So, instead of seeing
if the supervisor can see their subordinates,
we explore if all the
subordinates can see their supervisor
Both approaches have different
fields of view, but the
outside-in approach means that all fields-of-viewn now
have a common and shared focus
So the question was,
can we utilize this
for evaluating multiple lines of space within
the CADwalk environment?
We paired this with the fuel indicator,
so upon selecting an object into space
to place
a fuel indicator,
a virtual camera is also placed at that location.
The camera is then displayed on the end
looking back at the user
as they move around the space.
The user's controller is represented as a red
sphere on the wall
to give the user an understanding of where they are
based on the virtual cameras,
rendering. The user can place up to four virtual cameras in
the space based on where they place
fuel indicators in the space.
We conducted a user study to evaluate our work
with the primary goal of evaluating the two indicators,
and a secondary goal to explore
if our outside-in camera
approach was useful for end users. The
task required users to select a location
within a mock-up office scenario
that maximize the visibility to
four objects of interest.
There may not be a location in space
that had a hundred percent
visibility for those four objects, so it
was an optimization task, where they had to pick the best location
not the perfect location.
The data sets that we used for various room shapes
and configurations were
based on various
office configurations.
You can see on the right hand side
that the number of different shaped blocks sized based
on desks
filing cabinets, pillars, office dividers, etc.
We had five different conditions
and they were breaking down across two main aspects.
The first was the floor indicator.
We have the Baseline condition,
which was the original CADwoman visualisation.
We then had a single fuel indicator.
We then had multiple
few indicators where user
could select up to four objects
at the same time
to view the different indicators.
We then had
the Edge
renderings. And then
we had another condition that also utilized
multiple fuel indicators.
The second aspect of each condition
was related to what was showing on the wall
for the camera placement.
So, for the Baseline
this used a fixed camera
in the top left-hand side of the space
and this was looking back at the layout.
In a traditional
CADwalk session,
they would have a session operator
controlling this camera, but
because we were trying to have end-uses
take control of the system,
we had a camera located
a fixed position,
showing the entire space from that same location.
The single fuel indicator,
the multiple fuel indicator
and the edge conditions all shared
the same inside-out camera view
that was attached to the user's
handheld controller
and could be placed anywhere in the environment.
The Fifth condition that had the multiple
fuel indicators,
as well
then had four
outside in cameras
that could be placed at locations
selected by the user.
The data that we collected was participant location,
the direction they were looking at for their head
to evaluate whether they looking at the wall
or the floor,
the location selected the participant
as being the optimum location,
the visibility of the four objects of interest
from that location,
how often they placed or
removed the fuel indicators,
(if that was applicable for the condition),
We performed the
System Usability Scale
and collected experiences and preferences in the space
For full results,
please see the full paper.
For visibility, multiple-fuel indicator has significantly higher visibility
compared to the other conditions, and visibility
significantly improved across all the conditions
over time
as usets
it became more familiar with it. For completion time,
Baseline and Edgewood shown to be significantly faster
however, they did not differ from each other.
Looking at user movement through
the space,
multiple fuel indicators with, the traditional inside-out
camera, had significantly less movement than a single
fuel indicator.
However there was no variation
for the other conditions.
For mental effort, the Baseline had significantly higher
than the multiple
fuel indicator
with a traditional inside out view,
For SUS, all condictions except the Baseline received
above-average SUS scores. And again,
I please refer you to the paper to see
the full results.
For user preference, all conditions
were prefered by uses over the Baseline.
The multiple fuel indicator outside-in condition,
this is the new approach, was most preferred
but only significantly more than the
single fuel indicator inside-out. For takeaways,
we can see the Baseline leads to faster completion time
with less overall movement,
which is as expected.
The Baseline and edge
cues however, performed
worse for visibility
and all conditions were preferred over
the fundamental Baseline,
showing that we can actually improve
CADwalk.
There's this trade-off
between time and performance for visibility
versus the mental effort, required for those.
So we can have
a very quick scenario but the performance
will be low
visibility in the space
and they'll be a high mental effort in
that space.
Results show that there is a preference for the fuel indicator
based conditions,
versus The Edge
and the Baseline,
which is unsurprising,
given the quantitative nature of the fuel indicator.
The alternative views that we
introduced for the camera
placement showed promise
outside of the traditional outside-in view
Future work, should seek to address
this as a full study
in it's own, as we only partly explore
this as one condition
to reduce the number of conditions,
and thus the length of the study
for participants. We would like to know what this work was
funded as part of the Innovative Manufacturing
CRC. As part of the Australian
government's Department of Industry
science and energy and resources,
Cooperative Research Centre's program.
The authors would also like to thank
CADwalk Digital for their support
Thank you for listening