M. Ioannides (Ed.): EuroMed 2010, LNCS 6436, pp. 422–431, 2010.
© Springer-Verlag Berlin Heidelberg 2010
Teleimmersive Archaeology: Simulation and Cognitive
Maurizio Forte1, Gregorij Kurillo2, and Teenie Matlock3
1 School of Social Sciences, Humanities and Arts, University of California, Merced
2 Dept. of Electrical Engineering and Computer Sciences, University of California, Berkeley
3 School of Social Sciences, Humanities and Arts, University of California, Merced
Abstract. In this paper we present the framework for collaborative cyber-
archaeology with support for teleimmersive communication which aims to pro-
vide more natural interaction and higher level of embodiment. Within the
framework we create tools for exploration, interaction and communication of
archaeologists in a shared virtual environment. Users at different geographical
locations are captured by a set of stereo cameras to generate their real-time 3D
avatars. The proposed framework is intended to serve as a virtual simulation
environment where advanced behaviours, actions and new methodologies of re-
search and training in archaeology, cognitive science and computer science
could be tested.
Keywords: Cyberarchaeology, Teleimmersive Remote Collaboration, Shared
Virtual Environments, Cognitive Impact.
Teleimmersive Archaeology is a joint research project between the University of
Berkeley (Teleimmersive Lab) and the University of California, Merced (Virtual
Heritage Lab), supported by a CITRIS grant. The scope is the creation of virtual col-
laborative systems using teleimmersive technologies for real-time performances in the
interpretation and reconstruction processes in archaeology. The methodological
approach is based on the simulation process, in other terms on the idea that
cyber-archaeology constitute the core of the interpretation capabilities in the digital
simulation of the past (Forte, 2008).
One of the key issues in the collaborative-participatory activities is the role and the
behaviours of all the actors involved in the process. Therefore factors such as the
sense of presence, embodiment, gestures, interaction, motion capture, spatial sharing,
3D design and virtual tools influence deeply the level of learning and communication.
In the last decade several projects can be counted in this field: ARCHAVE
(Acevedo et al., 2001); VITA: Visual Interaction Tool for Archaeology (Benko et al.,
2004); SHAPE (Hall et al. (2001), LAVA, Laconia Acropolis Virtual Archaeology
(Getchell et al. 2009). In addition other projects have explored the educational potenti-
alities of the virtual communities such as Second Life (Nie, 2008). Further applications
Teleimmersive Archaeology: Simulation and Cognitive Impact 423
have been focused on the 3D Web collaborative systems such as the case of the FIRB
project (Forte and Pietroni, 2008), using Virtools DEV and Virtools Mutiuser Pack©
by linking three different archaeological sites. In this case, all collaborative activity
was online and with pre-determined 3D graphic libraries.
Although the massive multi-user environments seem appealing for such applica-
tions, they are currently unable to provide users with truly immersive experience or
sufficient flexibility to construct the type of complex framework that we propose. The
users of the former technologies were mainly observers of virtual replicas of ancient
worlds, not active participants contributing to the reconstruction and interpretation
Achieving an immersive experience in collaborative environments requires providing
a visual experience similar to that delivered by reality. Traditional immersive virtual
reality systems often use avatars, to represent human users inside the computer gener-
ated environments. Pre-modeled avatars, however, have several limitations with
respect to body movement dynamics, gestures, eye contact and other subtle communi-
cation via body language and facial expressions. Likewise, the existing video confer-
encing technologies fail to properly preserve the eye gaze which has been shown to be
an important factor for remote video-based communication (Fullwood and Doherty-
In our work we move further from the avatars and apply stereo reconstruction to
capture 3D representation of users in real time to facilitate visual experience similar to
reality (e.g. face-to-face meetings), where users are able to establish eye contact and
use their body to communicate and interact (e.g. pointing at objects). The developed
3D reconstruction framework has been successfully used previously in remote danc-
ing applications and learning of Tai Chi movements (Bailenson et al. 2008).
Fig. 1. Two users are interacting with a laser scanned statue in a shared virtual environment.
Integrated 3D video provides a virtual position of each user, allowing users to point at different
features of a 3D model as if they were sharing the same physical space.
424 M. Forte, G. Kurillo, and T. Matlock
3 Framework Overview
Our cyberarchaeology framework seamlessly combines computer vision and virtual
reality (Fig. 1). The prototype application supports rendering and interaction with
various 3D models, real-time interaction with different input devices, exchange of
multi-media data streams for communication (i.e. audio, video and 3D video). The
collaborative framework is built upon Vrui VR Toolkit, developed by Kreylos (2008)
at University of California, Davis, which can run on a wide range of virtual reality
hardware with support for different display and input device technologies.
3.1 Shared Scene Graph
The collaborative virtual environment is based on shared scene graph to describe the
spatial relationship of objects and facilitate interaction between remote users. The
scene graph is maintained on a central server which can connect to a spatial database.
Whenever changes are made to the scene (e.g. adding/deleting objects, moving ob-
jects etc.), the clients receives the updates for their local scene graph representations.
The scene graph also allows for efficient rendering. Current implementation with
vertex buffer objects allows for display of 1 million triangles with the frame rate of 60
FPS (GeForce GTX 8800 graphics card).
The scene graph encodes different properties of the scene (e.g. geometry, texture,
metadata) through a hierarchical scheme of inter-connected nodes of different types as
Transformation Node defines position and orientation of its child nodes with re-
spect to the other transformation nodes higher in the hierarchy. The transformation is
described with six parameters. Nested nodes allow objects to be linked together.
Geometry Node describes object geometry through a list of vertices and a list of
indices of the corresponding triangles. The data is used for building vertex buffer
Fig. 2. A simplified block diagram of the 3D teleimmersive application for collaborative
interaction in a shared virtual environment
Teleimmersive Archaeology: Simulation and Cognitive Impact 425
objects (VBO) which allow for efficient rendering. The geometry node also encodes
the object bounding box, which is used for the collision detection.
Texture and Material Nodes are comprised of object textures and material prop-
erties. Several high resolution texture file formats are supported in the application.
The textures can also be dynamically switched, for example to alternate between the
original and reconstructed surface of a wall painting. We implemented the surface
material properties defined by the OpenGL standards.
Object Node is a group node that can incorporate several geometry and tex-
ture/material nodes defining a particular object. The clients currently support only
OBJ/Wavefront 3D file format with the ability to use several different texture formats.
The object node can be easily extended to support other 3D formats by modifying the
file loading function.
Grid/Height Map Node is used to render surface grids for emphasizing different
surfaces or creating a height map that defines the landscape of the archaeological dig.
The map can be texture mapped with the images of the landscape to create more real-
Metadata Nodes support rendering of images and text that can be attached to dif-
ferent artefacts in the virtual environment. The metadata can contain information on
object geometry, location, short description, and images. Currently the metadata can-
not be edited within the application.
3.3 Navigation and Interaction
To explore the virtual environment, users navigate and interact with 3D models in the
first person perspective. The presence of the remote users is accomplished through the
rendering of their 3D avatar generated by the stereo cameras. The location of their
avatar corresponds to the current location of the user’s virtual view point.
Fig. 3. Locally, users observe the virtual world in the first person perspective. Remote users
are represented by their 3D avatars captured by one or more stereo cameras.
426 M. Forte, G. Kurillo, and T. Matlock
At any time, individual users can switch to the other user’s point of view or select
face-to-face mode for direct conversation. The latter functionality will bring the local
user in front of the remote user to facilitate a view similar to a video conferencing.
Remote users can, however, work independently in the shared virtual environment.
To prevent inconsistencies any two users cannot move the same object at the same
time. A lock is placed on the node and its children if another user is already interact-
ing with the object. The lock is assigned on first-come-first-serve basis.
The framework in connection with Vrui VR Toolkit features a wide selection of
tools for interaction with the environment:
Navigation Tools provide a variety of ways to move around the virtual environ-
ment (e.g. flying, surface navigation).
Measurement Tool can be used to perform dimensional and angular measure-
ments to capture the geometry of scanned objects. The measurement tools can also be
used to measure spatial relationships between the objects. Fig. 4(a) shows the meas-
urement of features on a small statue from a Western Han Chinese tomb.
Lighting Tool incorporates a virtual flashlight which can be used to relight parts of
the 3D scene or point at salient features. The relighting can enhance underlying de-
tails of the scanned artifacts. Fig. 4(b) demonstrates the use of a virtual flashlight to
enhance spatial details of a laser scanned model of a mask from Mayan city of Copan.
In the future we will add ability to place static lights along the scene to more precisely
control the illumination of the objects.
Annotation Tool allows users to draw 3D curves to mark different geometrical
features and communicate them to the remote users. The annotation tool can also be
used to quickly acquire a 2D or 3D sketch of patterns or objects. Fig. 4(c)(d) show an
example of sketching the pattern on a scanned tile of a Western Han Chinese tomb
and the corresponding geometry.
Dragging Tool is used to move objects in the 3D space. Object picking action is
determined through a collision detection algorithm between the dragging tool selec-
tion ray and pre-calculated object bounding box. User can interact with an object only
if another user has not already picked the same object. Movement of objects in differ-
ent direction can be controlled independently through a dialog (when using a mouse)
or through direct device interaction (when using 6 DOF input device). If the input
device tracking and the stereo cameras are aligned, the hand of the avatar will be in
contact with the object while it is being manipulated by the user.
Object Selector Tool is used to select objects and perform different actions related
to the local functionality, such as changing object rendering style (e.g. texture, no
texture, mesh only), retrieving object metadata, focusing current view to object prin-
cipal planes etc. The selector tool allows selection of several objects simultaneously
while different actions can be performed on selected objects.
3.4 3D Video Capture and Rendering
The avatars of users integrated with the virtual environment are created in real-time
by the 3D stereo algorithm (Vasudevan et al., 2010). This algorithm performs accu-
rate and efficient stereo computation by employing fast stereo matching through an
adaptive meshing scheme. The output of the stereo reconstruction is a 3D mesh which
is compressed and sent from each stereo camera to the local gateway. The achievable
Teleimmersive Archaeology: Simulation and Cognitive Impact 427
frame-rate is about 25 FPS on images of 320x240 pixels and about 12 FPS on images
of 640x480 pixels. The accuracy of the reconstruction and is typically between 1 cm to
3 cm. To increase the fidelity of the reconstructed users, we also apply dynamic texture
mapping. Several stereo views can be combined through calibration and blending to
increase the workspace of the interaction and to provide 360-degree capturing.
In this paper we present results from two different experimental setups (Fig. 5) con-
nected over the internet. For the first setup, we used the teleimmersion platform at
University of California, Berkeley (Vasudevan et al., 2010), which has several stereo
clusters, each connected to a four core server, to perform 360-degree stereo recon-
struction. The system is integrated with a tracking system (TrackIR by NaturalPoint)
that tracks position and orientation of a Wii Remote (Nintendo). The Wii Remote is
used as a 6 DOF input device for interacting with the virtual environment. The second
0.2 0.4 0.6
Fig. 4. (a) Dimensional and angular measurement can be performed on the virtual artefacts to
capture their geometry. (b) Remote user is interacting with a virtual flashlight to enhance the
underlying details of the laser scanned model of a mask from Mayan city of Copan. (c) Anno-
tation tool is applied to mark important features and communicate them remotely to other
collaborators. (d) Data from the annotations can be extracted in a form of a 3D sketch for
428 M. Forte, G. Kurillo, and T. Matlock
setup consisted of a single Bumblebee 2 stereo camera (Point Grey, Inc.) positioned
above 65” LCD screen. Users were able to interact with the environment with a 3D
mouse. Users can change the hardware platform by simply modifying a configuration file.
At this stage, we did some preliminary experiments with the 3D archaeological
data coming from a monumental Chinese Western Han Tomb (beginning of the first
millennium AD). We recorded and documented the tomb with 3D scanners in the
summer 2008 at Xi’an, China. The tomb, now closed to the public (because of serious
problems of conservation) after the excavation, is now accessible only virtually. For
the teleimmersive system, the tomb was reconstructed by laser scanner data and by
the integration of high res textures of mural painting and 3D models of funeral goods
(recorded by laser scanning), then re-contextualized in their original positions (Fig.
3). Even the corridor and the three chambers of the tomb have been studied in the
collaborative systems, especially the architectural elements, the organization of the
space and the relation between iconography, the funeral chambers, and the 3D model.
The use of lighting and measurement tools with the capacity to move, share and com-
pare the objects in the cyber space, to add visual layers and outlines in the wall paint-
ings have considerably increased the simulation factors and the faculties for data
interpretation. The involvement of different interactors in the cyberspace yielded new
perspectives in the dialectics of the interpretation process and its multivocality.
Fig. 5. Two different teleimmersive platforms for interaction with the virtual environment
(below) and their corresponding view in the virtual environment
3.6 Cognitive Impact
Cognitive scientists are studying how users interact and manipulate objects in this
system. They will track the use and development of the system with various methods
of investigation. In the end, the results will be used to develop robust learning tools
and to improve the design and use of the system. In one line of cognitive research, the
eye movements of multiple users will be tracked as they discuss objects and manipu-
late objects. Of interest will be how language directs the attention of users. In another
line of exploratory research on users, the utility of a pure first person view (no avatar)
and a pseudo-first person view (with avatar) will be tested. Here trade-offs related to
Teleimmersive Archaeology: Simulation and Cognitive Impact 429
allotment of attention, ease of use, and awareness are expected. For instance, because
of limitations due to cognitive load, users may visually attend to objects less when
they are using an avatar to represent themselves. This will of course have implications
for how well users learn material in the environment. However, ease of communica-
tion may be better with an avatar because users can point and use other gestures for
disambiguating the speech stream. In yet another line of research, we will investigate
how and when users point at objects (and locations of objects), including the consis-
tency of their pointing and the spatial characteristics of their pointing.
3.7 Learning Process
Teleimmersive environments afford many learning opportunities because they allow
users to collaborate remotely on many different types of projects. One obvious issue
to study is how easily users can learn new information presented in the environment,
and how to simplify or optimize the learning process. Setting up a robust environment
that enables shared learning will allow users to collaborate more efficiently and to
collectively learn further new material more readily in the future (for excellent discus-
sion of scaffolding in technological learning environments, see Pea, 2004).
For the first cognitive study, we will use the Chinese Western Han Tomb, which
was mentioned above, as learning environment. We will begin with a simple study
that offers users either a first person view (no avatar to represent the self) or a third
person view (avatar to represent the self). In each of these conditions, we will run 10
participants; each will randomly be assigned to either a director role or to an observer
role. After they enter the tomb and get used to the environment, directors will be told
to reconstruct funeral objects while the observer watches. To accomplish this task, the
director will use a set of tools provided in a separate window. In the first person con-
dition, the director will move his or her avatar to the objects, pick them up, and
assemble them. In the second person condition, the director will simply touch the
objects, pick them up, and assemble them. In this case, no avatar will be visible (to
anyone in the environment). To learn how to successfully put the objects together, the
director will look at a diagram that shows how the objects go together but no written
text (so there is no explicit order of actions).
The task will intentionally be difficult to engage and challenge the users, and to
adequately test for differences in performance. Directors will have as long as needed to
complete the task. The director will let the observer know when he or she is finished.
At that point, the observer will have to put the object together. Various methods will be
used to test the success of learning in the avatar versus no avatar instructional phase.
One prediction is that the first person condition, directors will take less time to
construct objects because the director will have a direct embodied experience and not
have to worry about how the avatar appears. In turn, the observer who worked with
the director in this condition should also perform the task more quickly. We also pre-
dict there will be fewer errors with the first person condition because there will not be
an avatar to distract the visual attention from the objects and how they are assembled.
Yet another prediction is that directors, and in turn, observers, will remember details
about the task better in the first person condition because more of their attention will
have been allotted to the objects and strategies involved in putting them together.
Together, these results will provide valuable information about the utility of the sys-
tem for learning, and cognitive impact.
430 M. Forte, G. Kurillo, and T. Matlock
Follow-up studies will be developed from this initial study. In one, we will cross
the avatar/no avatar condition with user. This will enable us to study efficiency of
learning with no avatar under any circumstances versus learning an avatar that can be
seen only by the director or only by the observer. We will also extend the initial study
to situations with multiple users, and in some cases, multiple users constructing an
object together. This will be important to developing a system that takes multiple
views and mental models into account. We will also test novice versus expert users of
the system to determine optimal modes of instruction given learning stages.
The system is in prototypal phase and needs significant work to improve the tools,
user interfaces and rendering. This learning platform will teach users how to interpret,
reconstruct and communicate archaeological datasets using all the information avail-
able in a virtual participatory form, for instance, photos, movies, maps, 3D models,
spatial data and texts. In the future, we will study the utility of interactions with
avatar/no avatar versus first person interaction. In later lines of research, the eye
movements of multiple users will be tracked as they discuss objects and manipulate
objects. Of interest will be how language directions attention. Finally we will investi-
gate how and when users point at objects (and locations of objects), including the
consistency of their pointing and the spatial characteristics of their pointing. We will
also study how well users remember materials they have learned in the environments
and how well this information is retained over time.
Finally, the study and analysis of a virtual reconstruction process in archaeology
will help the virtual community to re-contextualize and reassemble spatial archaeologi-
cal data sets, from the first draft version (data not yet interpreted) to the final commu-
nicative level. The research activity will involve a bottom-up approach, i.e., the
analyses of the archaeological remains as they were found on site, and a top-down
approach, i.e., the reconstruction/interpretation of the data by cultural comparisons (for
example architectural features, artefacts, frescos, styles, materials, shapes, and others).
Acknowledgements. We wish to thank Ram Vasudevan and Edgar Lobaton, Univer-
sity of California, Berkeley, for contribution on the stereo reconstruction and Zhong
Zhou, University of Beijing, for texture compression. We also thank Tony Bernardin
and Oliver Kreylos, University of California, Davis, for the implementation of the 3D
video rendering. For the models related with the Mayan city of Copan, we thank
Fabio Remondino, B. Kessler Foundation, Trento, and Jennifer von Schwerin, De-
partment of Art and Art History, UNM/ Research Fellow, International Institute for
Advanced Research “Morphomata”, University of Cologne, Germany. The project
Teleimmersive Archaeology is supported by a CITRIS grant.
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