3D Recording and Modelling in Archaeology and Cultural Heritage: Theory and best practices 9781407312309, 9781407341958

Table of contents :
Front Cover
Title Page
Copyright
TABLE OF CONTENTS
LIST OF FIGURES AND TABLES
INTRODUCTION
1. ARCHAEOLOGICAL ANDGEOMATICS NEEDS
2. AERIAL AND TERRESTRIAL LASER SCANNING
3. PHOTOGRAMMETRY
4. REMOTE SENSING
5. GIS
6. VIRTUAL REALITY AND CYBERARCHAEOLOGY
7. CASE STUDIES

Citation preview

This book derives from the authors’ experiences when lecturing and tutoring at various international summer schools on the themes of reality-based surveying and 3D-modelling in the fields of archaeology and cultural heritage. The contents of this work therefore cover all scientific (and other) aspects of the new 3D technologies in the heritage field, with theoretical sections, case studies, best practices and considerations.

Stefano Campana since 2006 he has been a faculty member of the University of Siena (Italy), in the Department of History and Cultural Heritage, where he has been engaged in teaching and research as Lecturer in Ancient Topography. He is specialized in landscape archaeology, remote sensing, GIS and mobile mapping. His work is focused on the understanding of past landscapes from prehistory to the present day, with particular emphasis on Late Antiquity and the Early Middle Ages. The principal context for his work has been Tuscany, but he has also participated in, and led research work, in the UK, Turkey, Palestine, and Turkmenistan. He has been very active in organizing international conferences, summer schools and has given seminars and lectures at numerous universities including Durham (UK), Berkeley (USA), Stanford (USA), Duke (USA), Beijing (China), Ghent (Belgium), Saragossa (Spain), and Port-au-Prince (Haiti). In 2011 was proposed and admitted as a Fellow of the Society of Antiquaries of London (FSA), and in 2012 he was invited onto the General Management Board (GMB) of HIST, the Governing Board of the International Centre on Space Technologies for Natural and Cultural Heritage, under the auspices of UNESCO and the Chinese Academy of Sciences.

3D Recording and Modelling in Archaeology and Cultural Heritage Theory and best practices

REMONDINO & CAMPANA (Eds)

Fabio Remondino received his PhD in Photogrammetry and Remote Sensing in 2006 from ETH Zurich (Switzerland), where he worked until 2007 as research assistant. Since 2007 he has been based at the Bruno Kessler Foundation (FBK) of Trento (Italy), where he leads the 3D Optical Metrology (3DOM) research unit. His research interests focus on automated data processing, sensor characterization and integration, as well as information extraction from image and range data. He has authored more than 100 scientific publications in journals and peer-review conferences, and he acts as reviewers of many Geomatics journals. He has organized 20 scientific conferences and 12 summer schools for knowledge and technology transfer. He is now serving as President of the ISPRS Technical Commission V on ‘Close-range imaging, analysis and applications’, President of the EuroSDR Technical Commission I on ‘Sensors, Primary Data Acquisition and Georeferencing’, and he is a member of the Executive Board of CIPA Heritage Documentation. Of the many projects and heritage sites he has worked on, particularly memorable have been Pompeii, Paestum, Copan, Etruscan Necropolis, Bamiyan, Machu Picchu, Jerash, and Angkor Wat.

BAR S2598 2014

3D RECORDING AND MODELLING IN ARCHAEOLOGY AND CULTURAL HERITAGE: THEORY AND BEST PRACTICES

Edited by

Fabio Remondino Stefano Campana

3D RECORDING AND MODELLING

B A R

BAR International Series 2598 2014

3D Recording and Modelling in Archaeology and Cultural Heritage Theory and best practices Edited by

Fabio Remondino Stefano Campana

BAR International Series 2598 2014

ISBN 9781407312309 paperback ISBN 9781407341958 e-format DOI https://doi.org/10.30861/9781407312309 A catalogue record for this book is available from the British Library

BAR

PUBLISHING

CONTENTS INTRODUCTION .................................................................................................................................................. 3 M. Santana Quintero 1 ARCHAEOLOGICAL AND GEOMATIC NEEDS 1.1 3D Modelling in Archaeology and Cultural Heritage – Theory and Best Practice ........................................... 7 S. Campana 1.2 Geomatics and Cultural Heritage .................................................................................................................... 13 F. Remondino 1.3 3D Modelling and Shape Analysis in Archaeology ........................................................................................ 15 J.A. Barceló 2 AERIAL AND TERRESTRIAL LASER SCANNING 2.1 Airborne Laser Scanning for Archaeological Prospection.............................................................................. 25 R. Bennett 2.2 Terrestrial Optical Active Sensors – Theory & Applications ......................................................................... 37 G. Guidi 3 PHOTOGRAMMETRY 3.1 Photogrammetry - Basic Theory ..................................................................................................................... 63 F. Remondino 3.2 UAV: Platforms, Regulations, Data Acquisition and Processing ................................................................... 73 F. Nex & F. Remondino 4 REMOTE SENSING 4.1 Exploring Archaeological Landscapes with Satellite Imagery ....................................................................... 89 N. Galiatsatos 5 GIS 5.1 2D & 3D GIS and Web-based Visualization ................................................................................................ 101 G. Agugiaro 6 VIRTUAL REALITY & CYBERARCHAEOLOGY 6.1 Virtual Reality, Cyberarchaeology, Teleimmersive Archaeolog .................................................................. 113 M. Forte 6.2 Virtual Reality & Cyberarchaeology – Virtual Museums ............................................................................ 129 S. Pescarin 7 CASE STUDIES 7.1 3D Data Capture, Restoration and Online Publication of Sculpture ............................................................. 137 B. Frischer 7.2 3D GIS for Cultural Heritage Sites: The QueryArch3D Prototype .............................................................. 145 G. Agugiaro & F. Remondino 7.3 The Use of 3D Models for Intra-Site Investigation in Archaeology ............................................................. 151 N. Dell’Unto

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LIST OF FIGURES AND TABLES F. Remondino: Geomatics and Cultural Heritage Figure 1. Geomatics and its related techniques and applications.......................................................................... 13 Figure 2. Geomatics techniques for 3D data acquisition, shown according to the object/scene dimensions and complexity of the reconstructed digital model...................................................................................................... 14 Figure 3. Existing Geomatics data and sensors according to the working scale and object/scene to be surveyed 14 R. Bennett: Airborne Laser Scanning for Archaeological Prospection Figure 1. Demonstration and example of the zig-zag point distribution when ALS data are collected using an oscillating sensor ..................................................................................................................... 26 Figure 2. Schematic of the key components of the ALS system that enable accurate measurement of height and location .......................................................................................................................................................... 26 Figure 3. Schematic illustrating the differences in data recorded by full-waveform and pulse echo ALS sensors .................................................................................................................................................................. 27 Figure 4. An example of “orange peel” patterning caused by uncorrected point heights at the edges of swaths. The overlay demonstrates uncorrected data which in the red overlap zones appears speckled and uneven compared with the same areas in the corrected (underlying) model ..................................................................... 27 Figure 5. An example of classification of points based on return which forms the most basic method to filter non-terrain points from the DSM.......................................................................................................................... 28 Figure 6. Two examples of common interpolation techniques: IDW (left) and Bicubic Spline (right) ................ 29 Figure 7. Comparison of visualisation techniques mentioned in this chapter ....................................................... 30 Figure 8. Angle and Illumination of a shaded relief model .................................................................................. 31 Figure 9. Different angles of illumination highlighting different archaeological features.................................... 32 G. Guidi: Terrestrial Optical Active Sensors- Theory & Applications Figure 1. Triangulation principle: a) xz view of a triangulation based distance measurement through a laser beam inclined with angle α respect to the reference system, impinging on the surface to be measured. The light source is at distance b from the optical centre of an image capturing device equipped with a lens with focal length f; b) evaluation of xA and zA ...................................................................................................................... 38 Figure 2. Acquisition of coordinates along a profile generated by a sheet of laser light. In a 3D laser scanner this profile is mechanically moved in order to probe an entire area ..................................................................... 39 Figure 3. Acquisition of coordinates along a different profiles generated by multiple sheets of white light........ 40 Figure 4. Acquisition of coordinates of the point A through the a priori knowledge of the angle α, and the measurement of the distance ρ through the Time Of Flight of a light pulse from the sensor to the object and back ...................................................................................................................................................................... 41 Figure 5. Exemplification of the accuracy and precision concepts. The target has been used by three different shooters. The shooter A is precise but not accurate, B is more accurate than A but less precise (more spreading), C is both accurate and precise .............................................................................................................................. 44 Figure 6. ICP alignment process: a) selection of corresponding points on two partially superimposed range maps; b) rough pre-alignment; c) accurate alignment after a few iterations ......................................................... 46 Figure 7. Mesh generation: a) set of ICP aligned range maps. Different colours indicate the individual range maps; b) merge of all range maps in a single polygonal mesh ............................................................................. 46 Figure 8. Mesh optimization: a) mesh with polygon sizes given by the range sensor resolution set-up (520,000 triangles); b) mesh simplified in order to keep the difference with the unsimplified one, below 50μm. The polygon sizes vary dynamically according to the surface curvature and the mesh size drops down to 90,000 triangles ................................................................................................................................................................ 47 Figure 9. Structure of the G Group of temples in My Son: a) map of the G area drawn by the archaeologist Parmentier in the early 20th century (Stern, 1942); b) fisheye image taken from above during the 2011 survey. The ruins of the mandapa (G3) are visible in the upper part of the image, the posa (G5) on the right, the gopura (G2) in the center, and the footprint of the holy wall all around .............................................................. 50 Figure 10. Handmade structures arranged on the field by local workers for locating the laser scanner in the appropriate positions: a) mounting the platform on the top of the structure surrounding the Kalan; b) laser scanner located on the platform at 7 meters above the ruins; c) multi-section ladder for reaching the platform;

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3D RECORDING AND MODELLING IN ARCHAEOLOGY AND CULTURAL HERITAGE

d) structure for elevating the scanner at 3m from ground. During 3D acquisition the operator lies in the blind cone below the scanner in order to avoid the laser beam trajectory ..................................................................... 51 Figure 11. Map of the hill where the G Group is located within the My Son Area, with the scanner positions for acquiring different structures highlighted by colored dots .............................................................................. 52 Figure 12. Sculpted tympanum representing Krishna dancing on the snakes, originally at the entrance of the kalan: a) 3D laser scanning in the “store room” of the museum; b) reality-based model from the 3D data ......... 52 Figure 13. High resolution capture of the Foundation stone through SFM: a) texturized 3D model measured through a sequence of 24 images shot around the artifact; b) mesh model of the central part of the stone with a small area highlighted in red; c) color-coded deviations of the SFM acquired points from a best-fitting plane calculated on the red area of b), clearly showing a the nearly 2 mm carving on the stone ................................... 53 Figure 14. Tangential edge error in 3D point clouds: the red points represent the incorrect data respect to the real ones (black-grey color) .................................................................................................................................. 54 Figure 15. a) Point cloud model of the Kalan cleaned and aligned in the same reference system; b) polygonal model of the Kalan with a decimated and watertight mesh .................................................................................. 54 Figure 16. Reality-based models of all ruins in the G group obtained from 3D data generated by a laser scanner at 1 cm resolution and texturized with the actual images of the buildings: a) G1, the main temple; b) G2, the entrance portal to the holy area; c) G3, the assembly hall; d) G4, the south building; e) G5; the kiosk of the foundation stone ................................................................................................................................................... 55 Figure 17. Reality-based models of eight of the 21 decorations found during the G Group excavations and acquired in the My Son museum. All these decorations have been acquired with a sampling step between 1 and 2 mm, and post processed in order to strongly reduce the significant measurement noise but not the tiniest details of their shapes. The visual representation in this rendering have been made with a seamless texture ...... 56 Figure 18. Virtual reconstruction of the G Group and its surrounding panorama starting from the reality-based models acquired through laser scanning and digital images ................................................................................. 57 Table 1. Laser scanner configurations planned for 3D data acquisition .......... 49 Table 2. Number of point clouds acquired at different resolution levels (first three columns), and total number of 3D points acquired during the whole 3D survey of the G Group and the related decorations (last column) ........................................................ 53 F. Remondino: Photogrammetry - Basic Theory Figure 1. The collinearity principle established between the camera projection center, a point in the image and the corresponding point in the object space (left). The multi-image concept, where the 3D object can be reconstructed using multiple collinearity rays between corresponding image points (right) ................................ 64 Figure 2. A typical terrestrial image network acquired ad-hoc for a camera calibration procedure, with convergent and rotated images (a). A set of terrestrial images acquired ad-hoc for a 3D reconstruction purpose (b) ............................................................................................................................................................ 67 Figure 3. Radial (a) and decentering (b) distortion profiles for a digital camera set at different focal lengths .... 67 Figure 4. 3D reconstruction of architectural structures with manual measurements in order to generate a simple 3D model with the main geometrical features (a). Dense 3D reconstruction via automated image matching (b). Digital Surface Model (DSM) generation from satellite imagery (Geo-Eye stereo-pair) for 3D landscape visualization (c) .................................................................................................................................................... 69 Figure 5. 3D reconstruction from images: according to the project needs and requirements, sparse or dense point clouds can be derived .................................................................................................................................. 70 Table 1: Photogrammetric procedures for calibration, orientation and point positioning .................................... 66 F. Nex & F. Remondino: UAV: Platforms, Regulations, Data Acquisition and Processing Figure 1. Available Geomatics techniques, sensors and platforms for 3D recording purposes, according to the scene’ dimensions and complexity ....................................................................................................................... 74 Figure 2. Typical acquisition and processing pipeline for UAV images ..........76 Figure 3. Different modalities of the flight execution delivering different image block’s quality: a) manual mode and image acquisition with a scheduled interval; b) low-cost navigation system with possible waypoints but irregular image overlap; c) automated flying and acquisition mode achieved with a high quality navigation system ................................ 77 Figure 4. Orientation results of an aerial block over a flat area of ca 2km (a). The derived camera poses are shown in red/green, while color dots are the 3D object points on the ground. The absence of ground constraint (b) can lead to a wrong solution of the computed 3D shape (i.e. ground deformation). The more rigorous approach, based on GCPs used as observations in the bundle solution (c), deliver the correct 3D shape of the surveyed scene, i.e. a flat terrain ........................................................................................................................... 78

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LIST OF FIGURES AND TABLES

Figure 5. Integration of terrestrial images (a) with oblique (b) and vertical (c) UAV acquisitions for the surveying and modeling of the complex Neptune temple in Paestum, Italy. The integrated adjustment for the derivation of the camera poses of all the images (d, e) in a unique reference system .......................................... 79 Figure 6. A mosaic view of the excavation area in Pava (Siena, Italy) surveyed with UAV images for volume excavation computation and GIS applications (a). The derived DSM shown as shaded (b) and textured mode (c) and the produced ortho-image (d) (Remondino et al., 2011). If multi-temporal images are available, DSM differences can be computed for volume exaction estimation (e)......................................................................... 80 Figure 7. A mosaic over an urban area in Bandung, Indonesia (a). Visualization of the bundle adjustment results (b) of the large UAV block (ca 270 images) and a close view of the produced DSM over the urban area, shown as point cloud (c, d) and shaded mode (e) ................................................................................................. 81 Figure 8. Approximate time effort in a typical UAV-based photogrammetric workflow..................................... 82 Table 1. Evaluation of some UAV platforms employed for Geomatics applications, according to the literature and the authors’ experience. The evaluation is from 1 (low) to 5 (high) .............................................................. 75 N. Galiatsatos: Exploring Archaeological Landscapes with Satellite Imagery Figure 1. Illustration of the spatial resolution property ........................................................................................ 90 Figure 2. The high radiometric resolution of IKONOS-2 (11-bit) allows for better visibility at the shadows of the clouds .............................................................................................................................................................. 91 Figure 3. The left part displays the spectral resolution of different satellites. The right part illustrates the spectral signature from the point of view of hyperspectral, multispectral and panchromatic images respectively............ 92 Figure 4. Illustration of the different spatial coverage or swath width (nominal values in parenthesis) (reproduced from http://www.asprs.org/a/news/satellites/ASPRS_DATABASE_021208.pdf – Last accessed December 2011) ................................................................................................................................................... 92 Figure 5. Classical and modern geospatial information system (reproduced from Konecny, 2003) .................... 96 Table 1. Landsat processing levels as provided .................................................................................................... 92 Table 2. Description of error sources (Toutin, 2004) ........................................................................................... 94 G. Agugiaro: 2D & 3D GIS and Web-Based Visualization Figure 1. Example of relational model: two tables (here: countries and cities) are depicted schematically (top). Attribute names and data types are listed for each table. The black arrow represents the relation existing between them. Data contained in the two tables is presented in the bottom left, and the result of a possible query in the bottom right. The link between the two tables is realized by means of the country_id columns ........................ 102 Figure 2. Raster (top) and vector (bottom) representation of point, lines and polygon features in a GIS .......... 103 Figure 3. Qualitative examples of different interpolation algorithms starting from the same input (left). Surface interpolated using an Inverse Distance Weighting interpolator (center) and a Spline with Tension interpolator (right) .................................................................................................................................................................. 106 Figure 4. Examples of network analyses. A road network (upper left), in which 5 possible destinations are represented by black dots, can be represented according to the average speed typical for each roadway (upper right), where decreasing average speeds are represented in dark green, light green, yellow, orange and red, respectively. The shortest route, considering distance, connecting all 5 destinations is depicted in blue (bottom left), while the shortest route, in terms of time, is depicted in violet (bottom right). These examples are based on the Spearfish dataset available for Grass GIS ................................................................................................ 107 Figure 5. Examples of visualization of GIS data. A raster image (orthophoto) and a vector dataset (building footprints) are visualized in 2D (left). A 3D visualization of the extruded buildings draped onto the DTM ..... 108 Figure 6. Example of Web-based geodata publication in 3D: by means of virtual globes, as in Google Earth, or in the case of the Heidelberg 3D project (http://heidelberg-3d.de) ................................................................ 109 M. Forte: Virtual Reality, Cyberarchaeology, Teleimmersive Archaeology Figure 1. Digital Hermeneutic Circle ................................................................................................................. 114 Figure 2. Domains of digital knowledge ............................................................................................................ 114 Figure 3. 3D-Digging Project at Çatalhöyük ...................................................................................................... 118 Figure 4. Teleimmersion System in Archaeology (UC Merced, UC Berkeley) ................................................. 119 Figure 5. Video capturing system for teleimmersive archaeology ..................................................................... 119 Figure 6. A Teleimmersive work session ........................................................................................................... 120

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Figure 7. Building 77 at Çatalhöyük: the teleimmersive session shows the spatial integration of shape files (layers, units and artifacts) in the 3D model recorded by laser scanning............................................................ 120 Figure 8. 3D Interaction with Wii in the teleimmersive system: building 77, Çatalhöyük ................................. 121 Figure 9. Clouds of points by time of phase scanner (Trimble FX) at Çatalhöyük: building 77 ........................ 121 Figure 10. Image modeling of the building 89 at Çatalhöyük ............................................................................ 122 Figure 11. Image modeling of the building 77 at Çatalhöyük ............................................................................ 122 Figure 12. 3D layers and microstratigraphy in the teleimmersive system (accuracy