Hello and welcome to our talk - my name is Weizhou Luo and I am Anke Lehmann.
We present our ongoing work on investigating document layout and placement strategies in
Augmented Reality for collaborative sensemaking.
This is joint work with Yushan Yang and Raimund Dachselt and all of us are from the Interactive
Media Lab Dresden.
Sensemaking and brainstorming are essential activities in many domains.
Currently, people rely on paper such as sticky notes for brainstorming, or traditional 2D
interface to organize images into folders for sensemaking.
We envision that AR can upgrade such a workflow by largely extending the display area while
keeping users aware of their collaborators and surroundings.
However, it is not clear how the physical surroundings might affect virtual content
placement for collaborative sensemaking?
For this purpose, we design a user study with 8 participants as 4 teams.
We compared two different room settings: a Fully-furnished room versus a Less-furnished
room for a collaborative image categorization task.
Moreover, we are interested in the content placement, spatiality and layout.
In the training session, participants got familiar with the two interaction techniques
for the study.
By using Ray-casting, participants can move, rotate or resize objects which are out of
reach.
In contrast, participants can directly manipulate by hand when objects are near them.
In the formal study, teams were asked to perform a card sorting task on 50 images of cars or
fruits within 20 minutes in an AR room.
Teams were asked to freely group and cluster these images and they should come up with
as many categories as possible.
On the upper row, you see teams were grouping images in the fully-furnished condition.
On the bottom row, we demonstrate two teams were working in the less-furnished condition.
Both room conditions and datasets were counterbalanced and each team finished both sessions.
Based on our analysis, we identify three different spatial layout patterns.
In the Panoramic-strip pattern, the images are mainly placed horizontally as a semicircle.
The distribution of clusters is partly far apart as large gaps between individual clusters
can be found.
In the semi-cylindrical pattern, the images are mainly arranged by using both horizontally
and vertically axes.
For instance, team 2 used the space from the floor to the top to form a semi-cylindrical
structure without considering the space of the side table and the orange wall.
In the furniture-based distribution pattern, the images are mostly arranged in several
separated clusters and sub-clusters based on the real-world furniture.
For instance, above or below the tables, or using the whiteboard,
or the cabinet.
In addition to the spatial layout we also observed spatial placement patterns, where
teams used the physical environment for placing their content.
For example, teams tend to use vertical planes.
As you can see in these short examples they used the door area as a defining space to
form a cluster, as well as the orange wall.
A few teams also used the whiteboard.
But the physical space here is smaller, this was used less frequently and mainly for small
clusters.
Participants also used the furniture for their placement, mainly the two side tables in the
room, as you can see in examples in the upper row.
Likewise, the cabinet was used to place a cluster above it, as seen in the bottom row.
One team also used the geometry of the cabinet for their subclusters - such as sport cars
above the cabinet, normal cars on top of the cabinet, and vans on the cabinet door.
To our surprise, some teams used unexpected places, such as the stone column as a natural
cluster separator, what can be seen in the example of the fruit dataset.
Or they used the free gaps between the two tables as an imaginary container to place
a cluster.
We also observed the usage of a temporary storage space, like the whiteboard area, or
the room center during the task.
The example on the left, shows how Team 1 temporarily placed some cars on the whiteboard,
which is highlighted here.
One by one, two users then took images from the whiteboard and assigned them to other
clusters in the AR room.
On the right side you can see team 2, which uses the center of the room to share pictures
with each other
In summary, our takeaway points are that participants tend to use the room’s vertical surface
and the room’s furniture.
In addition, we observed three different spatial layout patterns, and temporary storage spaces
for collaboration.
Thank you for your attention.
For more detail, please refer to our paper and our project website.