Avatar2Avatar: Augmenting the Mutual Visual Communication between
Co-located Real and Virtual Environments
Robin Horst
, Sebastian Alberternst
, Jan Sutter
, Philipp Slusallek
, Uwe Kloos
and Ralf D
German Research Center for Artificial Intelligence (DFKI), Saarbr
ucken, Germany
Reutlingen University of Applied Sciences, Reutlingen, Germany
RheinMain University of Applied Sciences, Wiesbaden, Germany
Mixed Reality, Video Avatar, Multi-user Environments, Low-cost, Knowledge Communication.
Virtual Reality (VR) technology has the potential to support knowledge communication in several sectors.
Still, when educators make use of immersive VR technology in favor of presenting their knowledge, their
audience within the same room may not be able to see them anymore due to wearing head-mounted displays
(HMDs). In this paper, we propose the Avatar2Avatar system and design, which augments the visual aspect
during such a knowledge presentation. Avatar2Avatar enables users to see both a realistic representation
of their respective counterpart and the virtual environment at the same time. We point out several design
aspects of such a system and address design challenges and possibilities that arose during implementation.
We specifically explore opportunities of a system design for integrating 2D video-avatars in existing room-
scale VR setups. An additional user study indicates a positive impact concerning spatial presence when using
One of the core aspects which connects areas of hu-
man mediated knowledge communication is the mu-
tual communication of humans. At that, the visual
aspect is the most crucial one because about 55% of
a communication is transported visually (Mehrabian
and Ferris, 1967).
When it comes to the usage of Virtual Environ-
ments (VEs), most VR setups constrain the commu-
nication due to wearing a closed VR HMD. This
leads to a lack of a mutual representation that can be
beneficial for co-located knowledge communication
(Bronack et al., 2008). As a consequence of using
such technology immersed learners cannot see non-
immersed educators even if they are located in the
same room. Thereby, the pedagogical presence, that
is of importance relating to specific learning method-
ologies (Rodgers and Raider-Roth, 2006; Bronack
et al., 2008; Anderson et al., 2001), is constrained.
An example is a class-room setting, where teachers
integrate HMD VR technology in their course. They
cannot be seen by the learners, even though they are
in the same room.
By referring to the model of visual awareness that
Benford et al. (1994) proposed concerning collabo-
rative VEs and applying it to our application space,
no focus is provided for the immersed learners. Their
nimbus (the space in which users can be seen by oth-
ers), however, is available for non-immersed educa-
tors, so that they visually can perceive the immersed
learners. But these non-immersed educators instead
cannot get insights in the VE that the immersed learn-
ers act in.
In this paper, we contribute a novel collaborative
Mixed Reality (MR) system and its design aspects,
called Avatar2Avatar. This system indicates to equal-
ize the described information discrepancy and to aug-
ment the mutual awareness to enhance pedagogical
presence. We show the feasibility, discuss design
challenges and illustrate the integration into an ex-
isting room scale VR setup. We focus on utilizing
low-cost VR technology so that e.g. costly hardware
or procedures as complex device-calibration are ex-
cluded in advance. We also draw conclusions about
the actual presence relating to our system, measured
after Schubert et al. (2001).
Although it is possible to enhances similar co-
presence environments with 3D representations in
real-time (e.g. (Sousa et al., 2017; Gugenheimer et al.,
Horst, R., Alberternst, S., Sutter, J., Slusallek, P., Kloos, U. and Dörner, R.
Avatar2Avatar: Augmenting the Mutual Visual Communication between Co-located Real and Virtual Environments.
DOI: 10.5220/0007311800890096
In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019), pages 89-96
ISBN: 978-989-758-354-4
2019 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
Figure 1: The setting of Avatar2Avatar: (a) virtual first-person point of view; (b) RGB-D camera attached to an immersed
learner for capturing co-located educators; (c) RGB-D camera to capture all collaborators in the setting; (d) overview screen
showing the virtual scene and realistic avatar representations; (e) co-located educator with tracker.
2017) we indicate that 2D video-avatar representa-
tions still provided enough visual and spatial clues
to support visual communication and increase spatial
presence within our learning use-case.
As the foundation of our work, we subdivide the
overall system design into two sub-system concepts
which work as distributed components – one for each
class of users (immersed learners and non-immersed
1. Virtual POV The immersed learners’ POV
get augmented by a captured overlay image of
the segmented collaborating non-immersed edu-
cators. This image is integrated into the VE as a
2D texture and then consequently rendered in the
HMD (Fig. 1 (a)). A head-mounted RGB+depth
camera prototype is utilized for this purpose.
2. Scene Overview An overview perspective of
the virtual scene and image-textures of the im-
mersed learners and the non-immersed educators
are composed and visualized on a large screen.
This screen is placed within the room where both
user-classes are co-located in. As a consequence,
educators can orient themselves with respect to
the virtual scene and visually communicate with
the immersed learners (Fig. 1 (d)).
Pioneering work by Benford et al. (1994) and Ben-
ford and Fahl
en (1993) proposes concepts and tax-
onomies that mostly aim for considering co-operative
VEs with regard to tele-presence. They are applied
in several systems. Especially in MASSIVE (Green-
halgh and Benford, 1995) the authors show how dif-
ferently users interact with mutual users with respect
to the avatar representation and the degree of immer-
sion. While users with graphical representations of
others keep a personal distance, users with text-only
presentation of the scene are perceiving space com-
pletely different. They lack notions of this natural
personal space.
Billinghurst and Kato (1999) introduce a co-
located MR system that provides a three-dimensional
browser. The system offers one single degree of im-
mersion for all users and does not support immersive
VEs. The presented augmented reality interface of-
fers users to collaboratively browse web pages by us-
ing natural voice and gestures. This paper shows that
with a rising degree of immersion and the tendency
towards augmented virtuality (Milgram et al., 1995),
the amount of visual perception of co-located users
quickly decreases. The nimbus of users stays unaf-
fected, but their focus gets diminished. Even recent
system designs for co-located or tele-presence collab-
orations, as One Reality (Roo and Hachet, 2017), il-
lustrate similar issues. The need of a system design
that could extend existing VEs and provide mutual
visual representation for users with asymmetrical dif-
ferent immersion is indicated here. In particular re-
lating to multi-user environments that support more
than one level of immersion this is not a trivial task,
since multiple hardware setups must be incorporated
in such system designs.
Our system generally relates to realistic avatar
representations. There already exist several concepts
and systems that deal with realistic human avatars.
Each of them uses a different approach due to their
area of application. Huang and Kallmann (2009) pro-
pose a system which focuses on realistic motions for
avatars. Lok et al. (2014) propose a system that cre-
ates the realism aspect of avatars through high physi-
cality. There also exists work (Kotranza et al., 2009)
which introduces a system to augment an immersive
VE by providing haptic aspects. Here, non-verbal
communication benefits from the realistic tangibility
of a virtual human avatar. In contrast to the above
we integrate the realism-aspect of our avatars through
real-time captured video textures of the co-present
HUCAPP 2019 - 3rd International Conference on Human Computer Interaction Theory and Applications
Figure 2: Compositional structure of the overall system design. The yellow shape depicts the system’s boundary, the red and
the green respectively a sub-system.
Current VR systems for collaborative environ-
ments similar to ours (Sousa et al., 2017; Gugen-
heimer et al., 2017) propose processes to integrate
real-time 3D aspects, as well. Gugenheimer et al.
(2017) on the one hand do not focus on avatars, but
on the interactions that are provided for the differ-
ent user-classes. Sousa et al. (2017) on the other
hand show opportunities and use-cases for both 3D
and 2D representations from video-streams for tele-
communication purposes. In the latter, a toolkit is
proposed that models displays as planar rectangular
static surfaces within the virtual room. Our work,
however, focuses on these limitations of the 2D avatar
integrations in VEs and proposes a system design for
flexible and non-static video-avatars.
Further work (Garau et al., 2003; Latoschik et al.,
2017; Roth et al., 2016) points out the needs for non-
verbal communication benefits for realistic avatars.
Therefore, we refer to work considering low-cost
technologies, like Kinect cameras or HTC Vive sys-
tems, which capture video textures and integrate them
into VEs (Slater et al., 2010; Nordby et al., 2016; Re-
genbrecht et al., 2017; Zhu et al., 2016; Lee et al.,
2006; Barmpoutis, 2013). Work by Lee et al. (2006)
which is, however, comparable to ours integrates 2D
avatars visible for only one class of users (the non-
immersed educators). The integration of such avatars
into the immersive part of the system (immersed
learners) or into an existing VR system is not men-
tioned in these examples.
Our system is used to visualize realistic avatar rep-
resentations of all users and the VE (Fig. 1 (d)) so
that collaborating non-immersed educators can see
it. Simultaneously, pictorial representations of non-
immersed educators are integrated in the immersive
VE. The immersed learners therefore are enabled to
perceive their collaborators while wearing the closed
HMD (Fig. 1 (a)).
The Avatar2Avatar system design is composition-
ally modeled in Fig. 2 using fundamental modeling
concepts (Kn
opfel et al., 2005). Here, we see how the
overall system (yellow boundary) is designed to be
run on two machines – each with a sub-system (green
and red boundary) which communicate over a local
network. The system is built from six components
(Fig. 2) which are described in detail in the next sec-
1. Synchronized Scene
2. Overview RGB+D
3. Overview Compositor
4. VR Scene
6. POV Compositor
All of the above modules can be classified into ei-
ther capturing the virtual scene (components 1 and
4), extracting people’s image (components 2 and 5) or
composing these with the virtual scene (components 3
and 6).
Avatar2Avatar: Augmenting the Mutual Visual Communication between Co-located Real and Virtual Environments
3.1 Capturing the Virtual Scene
We utilize compositing techniques to create two sepa-
rate textures: On the one hand, a full screen texture of
user representations and the virtual scene, to be drawn
on the external overview screen and on the other hand
a texture of non-immersed educators to be integrated
into the VE for the immersed learners. Therefore, we
incorporate color and depth information from the VE.
The modules VR Scene and Synchronized Scene ( 2)
provide this image-based data. To capture the neces-
sary information from the virtual scenes we point out
three tasks to be performed:
Camera Alignment – Since we compose real and
virtual footage, there must be an alignment of the
real and the virtual camera. For matching the cam-
eras’ rotation and position we use tracking provided
by the tracking system that is part of an HTC Vive
VR setup. Other parameters are approximated by ad-
justing the virtual camera so that no further optical
calibration is needed for the physical counterpart. Ex-
amples are the radial distortion of the optical lens and
extrinsic/intrinsic camera parameters (like the field of
Color Image Acquisition While we propose
a design that is based on low-cost technologies, we
make use of the game engine Unity, which is appro-
priate for the concept. A major challenge when ac-
quiring visual information from game engines is the
interference with the game loop. In this context, an
asynchronous real time texture read-back from the al-
ready frequented GPU is compulsory. The rendering
must be performed independently of the game loop so
that a continuous and consistent image stream can be
Depth Acquisition In contrast to simple color
image acquisition using virtual cameras, the function
of acquiring depth information must be provided, too.
To solve this issue a custom shader can be used to
write depth information into a separate texture. This
texture can asynchronously be read from the GPU the
same way the color image texture is read back. The
game loop which runs the existing VE remains unaf-
fected by this integration into our system design.
3.2 Capturing and Extracting Peoples’
To augment the mutual visual communication be-
tween real and virtual environments we propose to
integrate 2D images of peoples as video textures into
VEs that have different degree of immersion. For pro-
viding these realistic avatars we rely on real texture
representations which must be extracted from camera-
captured 2D images beforehand. This functionality
is provided by the Overview RGB+D and the POV
RGB+D modules ( 2).
For capturing RGB+D image resources, two Mi-
crosoft Kinects (1920x1080 RGB; 512x424 D; 30
fps) are utilized in the proposed system. A major
difference in terms of processing captured images
for either the overview screen or the virtual POV is
the segmentation of the peoples’ textures. For the
non-moving camera which captures the whole scene
(Fig. 1 (c) and Fig. 2 RGB+D Camera 2) the Kinect
API’s functionality can be used for segmentation.
The process that provides the textures for integra-
tion into the VE in contrast cannot rely on such APIs’
functionality. None offers the extraction of people
in images for a constantly moving camera, as it is
for simulating a first person POV. This segmentation
therefore is handled during the compositing step it-
3.3 Composing People and the Virtual
For compositing we differentiate between two mod-
ules, the Overview Compositor and the POV Com-
positor. They are responsible for composing the im-
age for the overview screen and the virtual first per-
son POV representation respectively. Both composi-
tor modules receive similar data from the Kinects and
the virtual scene to perform a depth compositing in a
similar way as proposed by Zhu et al. (2016). Since
there already exists work which proposes straightfor-
ward solutions to use consumer-oriented VR technol-
ogy to visualize immersed people and their VE on an
external screen (Zhu et al., 2016), we will focus on the
novel aspects of composing video textures into im-
mersive VEs:
Integrating Two Compositing Systems Our
system integrates the two compositing modules sim-
ilar to a client-server architecture. The final image
for the external screen is processed and rendered di-
rectly on the external screen. The texture for the VE
in contrast must be processed in the compositor and
then sent back to Unity, where additional composit-
ing steps are processed.
Extracting People based on Room-scale VR
Technology To handle the first-person POV sim-
ulation challenge, mentioned in the previous sec-
tion, we cannot use a common method as for the
overview screen (e.g. provided by the Kinect API).
In Avatar2Avatar we propose to segment them by
combining a virtual bounding box (BB) (Fig. 3 (a)).
The depth information is furthermore used to per-
form a first occlusion calculation by testing the depth
HUCAPP 2019 - 3rd International Conference on Human Computer Interaction Theory and Applications
Figure 3: Footage (a)-(d) for the compositor of the virtual POV (e) and footage (f)-(i) for the compositor of the overview screen
(j). a) shows the virtual bounding box of the educator (blue shirt). It is used with the color image (b), the corresponding depth
image (c) and the depth of the scene (d) to compose the texture of the educator into the view of the immersed learner (checked
shirt; (e)). A Kinect segmentation work-flow is incorporated in our system ((g), (h)) to compose textures of both persons with
the virtual scene ((f), (i)) and render them together on an external screen (j).
of virtual objects to the captured depth of the non-
immersed educators.
Composing Realistic Avatar Textures Into a VE
While the avatar texture here is already segmented
and occlusions with virtual objects are realistically
calculated (for counteracting false positive occlusion,
Tab. 1), it still must be integrated into the VE. There-
fore, we draw a 2D plane with dimensions of the tex-
ture at the position of the non-immersed educator and
apply the texture to it. As we capture the texture from
a first person POV of the immersed learner, we must
ensure that this texture is projected on a plane orthog-
onally to the virtual viewing direction, as well.
Another challenge is the projection of a three-
dimensional human body onto a single depth value.
We propose to track the non-immersed educator so
that the avatar texture plane can be positioned in the
corresponding position within the VE. Since we only
tested for occlusions from virtual objects it is hy-
pothetically possible that extremities of the learners
could reach out from this single depth point. These
extremities could then the other way around occlude
a virtual object instead. This cannot be processed be-
forehand due to the three-dimensionality of the virtual
scene. As a consequence, we propose to offset the
plane about the length of half an arm span towards
the immersed user. This is a trade-off between the
correct placement of the texture and what we refer to
as false negative texture occlusion (Tab. 1).
Table 1: Classification of the occlusion problem into
false/true negative/positive.
Pixel is in
front of the
Pixel is behind
the object
Pixel is drawn
in front of the
true positive false positive
Pixel is drawn
behind the ob-
false negative true negative
Compared to absence of mutual visual representation,
related work indicates that an existing and realistic
representation will improve the mutual visual com-
munication (see section 2. Since we integrate existing
VEs into our system, the impact of our concept on the
presence of immersed users is of interest. A negative
impact could negate the advantage of the augmented
communication at the expense of the presence.
The use-case of our study was set within a col-
laborative training scenario, where a non-immersed
trainer had to familiarize a trainee with a construc-
tion environment in the automotive section. New con-
struction procedures were to explain. A collaboration
with a robot assistant should be utilized by the im-
mersed trainee to solve the construction task.
Avatar2Avatar: Augmenting the Mutual Visual Communication between Co-located Real and Virtual Environments
4.1 User Study
The study involved 12 paid, voluntary participants
(7 male, aged 23 to 35 with Ø 26,5 and SD 3,34). The
procedure was based on the approaches in (MacKen-
zie, 2012). Participants were welcomed, filled out
demographics, then were asked to interactively ex-
plore the VE in cooperation with the experimenter and
finally were interviewed and filled out a post-study
The design of the study included a random distri-
bution of the participants into two groups (between-
group design) - the experimental group which used
the proposed enhancement of the visual communica-
tion and the control group which only used common
VR technology (an unextended HTC Vive setup). The
presence of the participants was measured for being
the dependent variable. The IGROUP Presence Ques-
tionnaire (IPQ
) was used. It subdivides the presence
into three units: spatial presence, involvement and ex-
perienced realism.
For analyzing the results of the experiment, we
conducted a two sample t-test, by assuming normal-
distribution on the data. Tests on separate aspects of
presence revealed a phenomenon concerning the spa-
tial presence. Three out of ve questions regarding
the spatial presence factor of the IPQ show a signifi-
cant difference in favor to the score of the experimen-
tal group for questions Sp2 (p-value ¡ 0,00001) and
Sp3 (p-value = 0,021028) with p ¡ 0,05 and Sp5 (p-
value = 0,076108) with p ¡ 0,10 (Fig. 4).
Observations and user statements have indicated
four phenomena: Five out of the six experimental
group participants mentioned that the Kinect rig was
uncomfortable to wear, particularly due to the weight
of the rig which was mounted at the head. Two partic-
ipants mentioned the infrequent cut off of the extrem-
ities of the avatars. One participant unexpectedly sig-
naled that it would be comfortable if the video avatar
visualization could be turned on and off by him- or
herself, depending whether help was needed or not.
All six participants of the experimental group explic-
itly expressed that they perceived the video avatar rep-
resentation of the co-located educator helpful.
4.2 Discussion
The results indicate an improvement of the spatial
presence of the participants that were in the experi-
mental group. Most critical of the qualitatively mea-
sured issues (cut off limbs and rig weight) can be at-
tributed to the specifics of the Kinect camera. This is
http://www.igroup.org/pq/ipq/index.php (June 18,
a critical aspect of the design, because other cameras
that deliver similar content (matched color and depth
content) have as well similar specifications. Since we
target a low-cost concept we exclude to use profes-
sional hardware to solve this challenge. A software-
based solution for addressing the differing aspect ratio
and resolution of the Kinect and the HTC Vive, for ex-
ample as a separate module within the system design
that handles multiple cameras, however, is appropri-
ate. The camera itself could alternatively be mounted
at the torso of participants so that the weight of the
camera will not be perceived as focused as on the
As we chose to represent users within the 3D VE
as a 2D textured plane, there surely are alternative
representations that could be of significance. The
study, however, indicates, that 2D video avatars of-
fered enough visual and spatial clues for all of our par-
ticipants to perceive corresponding information that
is necessary for mutual visual communication. Since
one participant remarked that the optionality of the
video avatar visualization would be helpful, this phe-
nomenon should as well be considered in future sys-
tem designs. Questionnaire comments and qualitative
observations during the experiment indicate that over-
all, participants were satisfied with Avatar2Avatar and
found it particularly helpful for the given collabora-
tive knowledge communication task.
During the implementation of the system there ap-
peared several issues that had to be solved. Since
the camera that simulates the POV is attached above
the real POV (eyes) of the user, there are challenges
of transforming the virtual human texture/objects into
the correct angle and position. This is negligible if
objects are farther away but attract more visual atten-
tion from close up. Furthermore, there exist obvious
visual quality issues, like artifacts, in the avatar tex-
ture (Fig. 3 (e) and (j)). These can be attributed to the
relatively low depth resolution of the Kinect, which is
only 512x424 pixels. While the majority of artifacts
could be eliminated using dilate and erode algorithms
for edge cleaning, the artifacts are accepted in favor
to ensure a stable 30 frames per second rate and low
latency of the compositors. Some artifacts also ex-
ist because the statistical model of the Kinect API’s
human recognition is not arranged to recognize users
with an HMD or even a Kinect rig on the head.
Another issue that exists due to Kinect specifics is
that the virtual POV augmentation cannot cover the
entire resolution of the HMD. It is calibrated to a part
in the upper middle of the view. Dependent on the
position, extremities of persons could be cut off the
texture. The reason for this is the different aspect ra-
tio of the Kinect image (1920x1080 pixels 16:9)
HUCAPP 2019 - 3rd International Conference on Human Computer Interaction Theory and Applications
Figure 4: Three items of the IPQ show significant difference in favor to score of the experimental group.
and the Vive HMD (one eye with 1080x1200 pixels
9:10). As usual, a small part is not at all in the view
of a single eye due to parallax of two eyes.
Finally, jittering of the virtual bounding box can
be seen which results in partially cutting body parts of
the human texture within the VE. This jittering occurs
due to interfering infrared rays of the two Kinects,
since they use the same wave length as the HTC Vive
Lighthouses. Depending on the distance to each other
and the orientation, more or less jittering appears.
In this paper we proposed the Avatar2Avatar system
and design, which augments the mutual visual com-
munication between co-located real and virtual envi-
ronments. Non-immersed educators are involved in
the VE by providing an overview about the virtual
scene and all users of the system, including them-
selves. These non-immersed educators therefore get
immersed on a low level which creates a base context
for mutual awareness. In terms of the visual aware-
ness model we provide a focus into the real environ-
ment for immersed learners that utilizes the nimbus
(Benford et al., 1994) as mentioned in section 1
of co-located non-immersed educators. Educators
get their already existing focus widened so that they
can simultaneously see both the real persons and the
virtual environment.
While we focused our work specifically on knowl-
edge communication between users within one phys-
ical room, it is of major interest for us to transfer our
system design to the field of telepresence. Therefore,
there will be several changes necessary regarding the
hardware. Especially the simulation of the dynamic
virtual first person POV will be challenging. Further
calibration of all devices would be necessary (as e.g.
in (Beck and Froehlich, 2017)), but which is at the
expense of the low-cost and consumer-oriented as-
pect of the setup. In the second room there must be a
hardware construction that moves the camera accord-
ingly to the immersed users POV in the first room and
vice versa. Prototyping such a construction and fur-
thermore restricting the set-up to low-cost consumer
hardware could have a significant impact on knowl-
edge communication sectors, like e-Learning or dis-
tance learning.
The work is supported by the Federal Ministry of Ed-
ucation and Research of Germany in the project Hybr-
iT (Funding number:01IS16026A). The work further-
more is minor supported by the Federal Ministry of
Education and Research of Germany in the project In-
novative Hochschule (Funding number: 03IHS071).
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HUCAPP 2019 - 3rd International Conference on Human Computer Interaction Theory and Applications