3D Archaeology at Çatalhöyük

 This is the twelfth in a series of posts exploring 3D modeling in Mediterranean and European archaeology. For more in this series click here. We hope these papers will start a discussion either in the comments of the blog or on Twitter using the #3DMedArch hashtag. 

Maurizio Forte, Duke University

Introduction

Digital documentation and visualization in archaeology include digital applications of computer graphic rendering and simulation involving data, models and spatial information produced by different integrated technologies of data capturing, virtual reconstruction and visual communication (Forte 2010; Forte and Kurillo 2010; Forte and Siliotti 1997; Forte 2012). In the last decade the use of digital technologies on archaeological sites has exponentially grown at different scales and for different purposes: GIS, mapping, 3D modeling, remote sensing applications and digital photogrammetry. A really revolutionary approach in the archaeological documentation (on and off site) has been the introduction of image modeling techniques (with software like, for example, Photomodeler and Photoscan) for 3D data recording by DSLR cameras. In short, the archaeological models are generated by the overlapping of a sequence of high-resolution digital photos taken by uncalibrated cameras (Forte 2012). The relevant increasing of digital resolution in SLR cameras (over 15-20 mp) has also allowed the achievement of very interesting results in terms of 3D accuracy, performance and speed of data processing. In fact, the application of entry-level, intra-site 3D-technologies has fostered the community of archaeologists to consider 3D not just an “expensive” option, but a very affordable facility, also for the production of additional documentation, such as maps, sections, profiles, volumetric analyses and so on with a high level of accuracy. For example, our tests at Çatalhöyük have demonstrated that in a 3D model of a Neolithic house (around 25 square meters) (generated by the software Photoscan) the accuracy is about 4-5 mm (Forte 2012).

Visualizing Çatalhöyük

Çatalhöyük is a Neolithic site located in Central Anatolia and it is considered one of the “first cities of the world” (fig.1). Excavated by James Mellart from the ‘60s and then from Ian Hodder from the 80s, Çatalhöyük has been for a long time as a special place for the experimental introduction of new methodologies and theoretical approaches in archaeology such as multivocality, post-processualism and, more recently, cyber-archaeology and new media (Hodder 1989; Hodder 1990; Hodder 2006; Hodder, et al. 2007). The site, dating from 7400-6000 B.C is made up of two mounds: Çatalhöyük East and Çatalhöyük West. Çatalhöyük East consists of 21m of Neolithic deposits. Çatalhöyük West is almost exclusively Chalcolithic (6000-5500 B.C.), located in a different position and showing evident social-cultural changes in the settlement and territory organization. The two mounds span 2000 years and show an impressive urban continuity though time whereas the house is the social-cultural-urban pattern of the system: ritual, domestic and symbolic space in the same time.

Figure 1

Çatalhöyük was discovered in the 1950s by the British archaeologist James Mellaart (Mellaart 1967) and it was the largest known Neolithic site in the Near East at that time. Important events such as the domestication of plants, invention of pottery in connection with the large size and dense occupation of the settlement, as well as the spectacular wall paintings and other art forms that were uncovered inside the houses made it very famous internationally. The houses had no doors to the outside (main entrance from the roof), and the inhabitants buried their dead under the floors of their platforms. Despite several decades of study and excavation, the diachronic urban development of the site is still very controversial and it needs more studies and analyses in relation with the landscape and the symbolic, ritual and social use of the buildings. The site was inscribed in the UNESCO World Heritage list in 2012. 

The 3D-Digging Project

The 3D-Digging Project started at Çatalhöyük in 2009 with the intent to digitally record in 3D all the archaeological stratigraphy in some areas of excavation using an integrated approach (different devices and technologies) for virtually reconstructing all the process in desktop and virtual reality systems. The 3D documentation is not yet a standard in archaeology but it can change the hermeneutic outcome of an excavation since it is able to create new interpretations and research questions because of 3D connections, simulations and interactive modeling. A first experiment of 3D recording of ritual figurines by optical scanner (Nextengine; figs.2-3) started in 2009: the models were originally recorded in semi-automatic way by the scanner, then optimized in Meshlab and finally printed in three dimension (fig.3).

Figure 2

Figure 3

In this preliminary phase the project was aimed at the comparison and study of different kinds of laser scanners (based on different technologies and settings) in order to understand their performance in relation to the project goals (see table below).

 

The first questions/issues arising from this analysis were mainly focused on the level of accuracy and scale of representation for the models. Optical and time of flight scanners, in fact, have different performance and technical features. Optical scanners work in a range of microns (about 300,000 pts per second, the Minolta), time of flight scanners in a range of mm/cm. 

In the 3D-Digging Project the strategy was to make comparative testing involving optical, time of flight, and shift-phase scanners (see table 1) in order to understand the performance of the scanners and accuracy in relation to archaeological information. For example, details of stratigraphic surface or micro-morphologies are not visible by naked eye or with other means. For archaeological stratigraphy we have tested the Minolta 910 (optical), Trimble GX (time of flight), Trimble FX (shift-phase) and Faro Focus 3D (shift-phase). 

In 2010 the first experiment was undertaken with the Minolta 910 for recording all the excavation layers in a “midden” area (fig.4). “Midden” areas at Çatalhöyük correspond to accumulation of rubbish outside the living areas and can indicate social/collective activities made for different scopes (construction works, dedicated place for rubbish, etc.). The initial idea was to use an optical-triangulation scanner (Minolta 910) for stratigraphy in order to visualize and better study micro-layers (Shillito L.-M 2011), since they are not easily identifiable with an autopsic experience (figs.5-7).

Figure 4

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Figure 6

Figure 7

In 2011, we have adopted two systems working simultaneously for data recording: a new time of shift-phase scanner (Trimble FX) and a combination of camera based software of computer vision and image modeling (Photoscan, stereoscan, Meshlab). The Trimble FX is a time of shift-phase scanner able to generate 216000 pt/sec and with a 360 x 270* field of view; it is a very fast and effective scanner with the capacity to generate meshes during data recording, so that to save time in the phase of post processing (fig. 8). The strategy in the documentation process was to record simultaneously all the layers/units in the sequence of excavation using laser scanning and computer vision. At the end of the season we have generated 8 different models of the phases of excavation by computer vision (3D camera image modeling, figs. 9-10) and as well by laser scanning (figs.11-13). All the 3D models were available on daily basis for interactive visualization and spatial analysis. The scheme below shows the principal features and differences between the two systems; laser scanning requires a longer post-processing but it produces higher quality of data. Computer vision allows to have immediate results and to follow the excavation process in 3D day by day but not with the same geometrical evidence of the laser scanner. 

Figure 8

Figure 9

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Figure 11

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Figure 13

The digital workflow for the computer vision processing is based on 1) photos alignment; 2) construction of the geometry (meshes) 3) texturing and ortophoto generation. The accuracy by computer vision measured in 2011 models was around 5 mm. The use of georeferenced targets on site was implemented for the automatic georeferencing of 3D models with the excavation grid. In that way all the 3D information recorded during the excavation is perfectly oriented and integrated with all the 2D maps, GIS layers and archeological data. The speed of this process has allowed daily discussions on the interpretation of the archaeological stratigraphy and on 3D spatial relations between layers, structures and phases of excavation. In addition, the excavation of an entire building (B.89) has allowed testing the system in one single context so that to produce a 3D multilayered model of stratigraphy related to an entire building. The excavation of a Neolithic house is an ideal case study for testing 3D data recording and puzzling of a multi-stratigraphic context since it is possible to visualize and investigate post-depositional and depositional phases related to the life and the abandonment of a building (construction works, foundations, rituals, domestic activities and so on). Moreover, the B89 is a quite big house, well-preserved and with a very interesting stratigraphy (fig.9).

The current workflow allows every team managing independently almost all the phases of digital data recording on site and to interpret the data directly in lab at the end of the day: by computer vision, 3D sketching, 3D visualization. The software used for 3D modeling is Meshlab, Photoscan, 3D Studio Max; for 2D mapping is ArcGIS, QGIS, OpenJump, Autocad, Meshmixer. All the 3D models are georeferenced and exportable in different spatial software and platforms. After 3 years of fieldwork, the digital workflow is robust and consistent: computer vision (shape from modeling) is undoubtedly the most effective, user friendly and robust technique in intra-site contexts. The fact that involves the use of standard digital cameras (from 8 to 24 Mpixels) and very low cost and open source software (Photoscan and Meshlab, QGIS), makes all the pipeline very portable and usable sharing the same technologies. At Çatalhöyük computer vision is typically used at intra-site level for data recoding of buildings, layers, units, features and burials (fig.14), while laser scanning also at inter-site scale.

Figure 14

More specifically, the 2012 fieldwork season have involved different scales of data recording: artifacts by optical scanner (microns accuracy); stratigraphic units by computer vision (accuracy: 0.5-1 cm); buildings and features by time of phase laser scanning (accuracy: 3-5 mm); large scale models (South and North shelters) by time of phase laser scanners (0.5 cm). 

The systematic use of computer vision and 2D photogrammetry for data recording of burials was extremely successful for the osteologists’ team coordinated by Scott Haddow (fig.14). Indeed, in 2012 it was possible to record and reconstruct in 3D twenty-one burials with related 2D drawing of skeletons and other features (fig.14). In this case the digital workflow involves computer vision for the generation of 3D models, 2D and 3D georectification, 2D drawing of the burials in CAD (Librecad) and finally their implementation in ArcGIS as digital maps (raster-vector) and 3D models (3ds).

For the building 89, 3D data recording has followed the procedure of single context excavation: every 3D model was generated in relation to the identification and classification of stratigraphic units. Finally, all the 3D models of B89 were aligned and georeferenced (total 25 phases in 2011-2012)  in Meshlab and ArcGIS.

The DiVE – Duke Immersive Visualization Environment

The digital workflow established during the excavation was able to generate a relevant amount of data in the format of point clouds, 3D models, textures and metadata, all georeferenced in the same space. Interaction and use of 3D models are crucial for data interpretation on site but also during a simulation process during a lab session. A quite complicated issue concerns how it is possible to make all this digital process completely reversible. In other words: how can we browse layers, stratigraphy and artifacts in a virtual reality system? How can an immersive embodiment be used for a virtual digging? During the excavation all the data have been processed and visualized in Meshlab: this software includes in fact many tools for data processing, meshing, merging and visualization by layers. However a higher level of 3D processing was needed in order to better study the 3D connections of models and layers.

With this premise in mind, all the models made by laser scanners and computer vision have been optimized and implemented for the DiVE, the Duke Immersive Visualization Environment at Duke University (fig.15). The DiVE is a research and education facility dedicated to exploring techniques of immersion and interaction: it is the fourth 6-sided CAVE-like system in the United States (figs.15). The DiVE is a 3m x 3m x 3m stereoscopic rear projected room with head and hand tracking and real time computer graphics. All six surfaces – the four walls, the ceiling and the floor – are used as screens onto which computer graphics are displayed. The DiVE offers a fully immersive experience to the user, who literally walks into the virtual world. The user is surrounded by the display and can interact with virtual objects: stereo glasses provide depth perception, and a handheld “wand” controls navigation and virtual object manipulation. This digital immersive embodiment increases the sense of presence of the user in the virtual domain, fostering the identification of affordances and 3D connections, otherwise non visible in the real world.  

Figure 15

The entire B.89 was virtually reconstructed in the immersive system including all the stratigraphic layers excavated in 2011-12. The handheld “wand” controls navigation allows interacting and browsing layers, models and artifacts in 3D, using a 3D menu. The tracking system connected with stereo glasses drives the visualization according to the head position of the user. In this way, the virtual exploration augments the sense of presence in the virtual environment. The first tests inside the DiVE concerning the visualization and interaction of the Neolithic house, B89, have been quite successful: the 6 sided CAVE rescale the virtual building in a very realistic way, giving the users a very immersive sense of space and the feeling to be in the mid of the excavation “pod”. The interaction with different layers and stratigraphy “from inside” creates a specific “archaeological” embodiment, where the users can discuss and see data/models in transparency (fig.15). In addition, the B89 was also virtually reconstructed as it is assumed it was originally with plaster, floor, decorations, roof and interior architecture. The virtual reconstruction overlays the structures of the building as they appear today by laser scanning recording. In this way it is possible to compare the potential original physiognomy of the building with the structures explored during the excavation.

Since the DiVE can host even 6-7 people simultaneously, it is possible to organize presentation for small classes or research working groups. Indeed, at Duke we started to schedule small groups  and classes discussions about principles of archaeological stratigraphy, architectural features of Neolithic houses, depositional and post-depositional events, also in preparation to the summer fieldwork.

Acknowledgments

Trimble Navigation, Scott Haddow, Stefano Campana, Gianfranco Morelli and all our students for their dedication and efforts in the excavation and in the participation to the 3D-Digging Project. Special thanks to Elisa Biancifiori, Francesca Paino and Matteo Pilati for their contributions to the success of the project.
First experiment of optical scanners (Minolta 910) on 3D stratigraphy : Fabrizio Galeazzi, UC Merced
Time of flight laser scanning data recording coordinated by Nicola Lercari, Duke University
Virtual preliminary reconstruction of B89 made by Rebecca Lai, Duke University
Computer vision and shape from modeling coordinated by Nicolo’ Dell’Unto, Lund University.

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