An Open Source solution for Three-Dimensional documentation: archaeological applications

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The modern techniques of Structure from Motion (SfM) and Image-Based Modelling
(IBM) open new perspectives in the field of archaeological documentation, providing
a simple and accurate way to record three dimensional data.
The software Python Photogrammetry Toolbox (PPT) is an Open Source solution that
implements a pipeline to perform 3D reconstruction from a set of pictures. It takes
pictures as input and performs automatically the 3D reconstruction for the images for
which 3D registration is possible.
It is composed of python scripts that automate the different steps of the workflow.
The entire process is reduced in two commands, calibration and dense reconstruction.
The user can run it from a graphical interface or from terminal command. Calibration
is performed with Bundler while dense reconstruction is done through CMVS/PMVS.
Despite the automation, the user can control the final result choosing two initial
parameters: the image size and the feature detector. Acting on the first parameter
determines a reduction of the computation time and a decreasing density of the point
cloud. Acting on the feature detector influences the final result: PPT can work both
with SIFT (patent of the University of British Columbia - freely usable only for
research purpose) and with VLFEAT (released under GPL v.2 license). The use of
VLFEAT ensures a more accurate result, though it increases the time of calculation.
Python Photogrammetry Toolbox, released under GPL v.3 license, is a classical
example of FLOSS project in which instruments and knowledge are shared. The community works for the development of the software, sharing code modification,
feed-backs and bug-checking.

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An Open Source solution for Three-Dimensional documentation: archaeological applications

  1. 1. AIUM 2012 «ARCHEOLOGY INTERNATIONAL UNIVERSITY MEETING» 8th-10th NOVEMBER 2012 An Open Source solution for Three-Dimensional documentation: archaeological applicationsGiulio BigliardiCGT-Centro di GeoTecnologie (Univ. di Siena)bigliardi2@unisi.itMarta BottacchiCGT-Centro di GeoTecnologie (Univ. di Siena)bottacchi@unisi.itSara CappelliCGT-Centro di GeoTecnologie (Univ. di Siena)cappelli11@unisi.itLeonardo CarmignaniDipartimento di Archeologia e Storia delle Arti –Sezione di Preistoria e Protostoria (Univ. di Siena)leocarmignani@msn.com
  2. 2. Digital models are nowadays present everywhere,their use and diffusion are becoming very popularthrough the Internet and they can be displayedon low-cost computers.Although creating a simple 3d model seems to bequite simple, actually the generation of a preciseand photo-realistic computer model of a complexobject still requires considerable effort.Three-dimensional digital models are required inmany applications such as inspection, navigation,object identification, visualisation and animation.
  3. 3. Recently it has become a veryimportant and fundamental stepespecially for cultural heritage digitalarchiving. The aims are different:documentation in case of loss ordamage, virtual tourism andmuseum, education resources,interaction without risk of damage,and so forth.The specific requirements for manyapplications, including digitalarchiving and mapping, involve highgeometric accuracy, photo-realism ofthe results and the modelling of thecomplete details, as well as theautomation, low cost, portability andflexibility of the modelling technique.
  4. 4. Three-dimensional modelling of objectsand scenes is an intensive and long-lasting research problem in the graphic,vision and photogrammetriccommunities.3D Digital copy can be done by differenttechnology, laser (ground), lidar(aerial), photogrammetry. Lidar Nowadays the most common geomatics techniques used for 3D documentation, reconstruction and interpretation process in the archaeological field are based on image data (e.g. photogrammetry) or range data (e.g. active sensors such as laser scanners). Both approaches have their own advantages and disadvantages and generally the choice between them is made according to the budget, project size and goal, required degree of detail Laser Scanner and experience of the working team.
  5. 5. Image-Based Modelling and Structure from MotionNowadays 3D scanners are also becoming astandard source for input data in manyapplication areas, but the modern techniquesof Structure from Motion (SfM) and Image-Based Modelling (IBM) open new perspectivesin the field of archaeological documentation,providing a simple and accurate way inrecording three-dimensional data.In computer graphics and computer vision,Structure from Motion (SfM) and Image-BasedModelling (IBM) methods rely on a set of two-dimensional images of a scene to generate athree-dimensional model.Compared to laser scanners, the mainadvantages of SfM and IBM are that thesensors are generally cheaper and portableand that 3D information can be accuratelyrecovered regardless of the size of the object.
  6. 6. Python Photogrammetry Toolbox (PPT) From a set of images…The Python Photogrammetry Toolbox(PPT) is an open source system thatimplements a pipeline to perform 3Dreconstruction from a set of pictures.It takes pictures as input and performsautomatically the 3D reconstruction forthe images for which 3D registration ispossible.It is done by identifying similar contentbetween N images and solve 3Dgeometry problems.User input consist of an image collectionand camera parameters. The computedoutput is a 3D points cloud. …to a 3D points cloud
  7. 7. Python Photogrammetry Toolbox (PPT) and its Graphical User Interface (PPT-GUI) isdeveloped by Alessandro Bezzi (ArcTeam – Trento, Italy) and Pier Moulon(IMAGINE/LIGM, University Paris Est & Mikros Image).The suite Python Photogrammetry Toolbox (PPT) is composed of python scripts thatautomate the different steps of the workflow. The entire process is reduced in twocommands: camera calibration and dense 3D points cloud reconstruction. PPT-GUI is the graphical interface to interact easily with the photogrammetry toolbox. The interface is designed in two different parts: a main window composed by numbered panels which allows the user to understand the steps to perform…
  8. 8. …and a terminalwindow in which theprocess is running.
  9. 9. RunBundler performsthe camera calibrationstep.Bundler is a structure-from-motion (SfM)system written in Cand C++ forunordered imagecollections.It computes the 3Dcamera pose from aset of images. Itneeds only twoparameters: cameramodel and sensorwidth size.
  10. 10. Despite the automation, the user can control the final result choosing two initialparameters: the image size and the feature detector. A reduction of the computation time and a decreasing density of the 3D points cloud depend from the setting of the first parameter. It is a scaling factor of the image size.
  11. 11. Despite the automation, the user can control the final result choosing two initialparameters: the image size and the feature detector. The final result depend from the setting of the feature detector: PPT can work both with SIFT (patent of the University of British Columbia - freely usable only for research purpose) and with VLFEAT (released under GPL v.2 license). The second one is completely open source, it ensures a more accurate result, but it increases the time of calculation.
  12. 12. RunCMVS takes theoutput of structure-from-motion (SfM)software as input, andperform the dense 3Dpoint cloudcomputation.Data conversion fromBundler format toCMVS/PMVS format ismade by usingBundle2PMVS andRadialUndistort.
  13. 13. Dense computation is done by PMVS as well as CMVS, that is an optional process that divides the input scene in many smaller instance making the process of dense reconstruction faster.The main drawback of PPT is that computation speed depends from userscomputer. There could be some more drawbacks for large scenes or large imagesbut a compromise between performance and quality can be made by reducingimage size with the scaling factor. Generally, the amount of time needed for theprocessing of image sets is in the order of hours.
  14. 14. MeshLabThe 3D points cloud processed by PPT is displayed and processed in MeshLab.MeshLab is an open source system to create a 3D surface (mesh) from a 3D pointscloud (http://meshlab.sourceforge.net/).MeshLab is developed by Visual Computing Lab of Rome (ISTI-CNR) and is designedwith the following primary objectives:• ease of use. The tool should bedesigned to facilitate users withouthigh 3D modeling skills• single mesh processing oriented.The system should try to stayfocused on mesh processing insteadof mesh editing and mesh designwhere a number of other applicationsexist a (notably blender, 3D Max,Maya, and many others)• efficiency. 3D scanning mesh caneasily be composed by millions ofprimitives (points…), so the toolshould be able to manage them
  15. 15. From a set of images… …to a 3D points cloud with PPT …to a 3D model with MeshLab.
  16. 16. Points cloud… …mesh…The point cloud can be cleaned ofoutliers, cropped to the area ofinterest and then triangulated usingone of the merging filters available inMeshLab.The result is a 3D surface. The colourof the surface (texture) may bederived from the 3D points cloud,which is usually coloured. …3D model with photorealistic texture.
  17. 17. Step 1: import the points cloud
  18. 18. Step 2: cleaning the points cloud
  19. 19. Step 3: surface reconstruction (Poisson or Ball Pivoting approach)
  20. 20. Step 4: coloring the mesh using the color of the 3D points cloud
  21. 21. The 3D model
  22. 22. Archaeological applications: FindsArchaeological finds can be documented “in situ”, taking pictures moving aroundthe object, or in laboratory.In this case 9 pictures were taken with a NIKON Coolpix L110 at 12 MP.
  23. 23. Archaeological applications: FindsArchaeological finds can be documented “in situ”, taking pictures moving aroundthe object, or in laboratory.In this case 9 pictures were taken with a NIKON Coolpix L110 at 12 MP.In PPT the image were elaborated In MeshLab the mesh was createdwith the feature detector VLFEAT and with the Poisson surfacewith a scaling factor of 0.75. reconstruction filter (octree depth 10, solver divide 9) and the coloured.
  24. 24. 3 cmThe real object
  25. 25. 3 cmThe real object excellent quality for both of details and texture
  26. 26. Archaeological applications: LayersArchaeological field activity is mainly a working process which ends, in mostcases, with the complete destruction of the site. Since most of the interpretationis performed in a second stage, it is necessary to collect a massive amount ofdocumentation (images, sketches, notes, measurements).In the lack of particular expensive equipment (laser scanner, calibrated camera)or software (photogrammetric applications), field documentation is composed bypictures, manual drawings, total station measurements and photo-mosaics. While3D scanning technologies are able to precisely capture the geometry of theexcavation, their cost and operational time discourage an intensive field use.The alternative is represented by Image-Based Modelling and Structure fromMotion technologies, which are able to obtain a 3D model of an element startingfrom a set of images. Using the same instruments of standard archaeologicaldocumentation (digital camera and total station) it is possible to record also themorphology of the level. The data acquisition is fast and simple and it consistsexclusively in taking pictures of the area of interest. The same rules of thetraditional photography are to be followed: centre the desired object in eachpicture, avoid extreme contrast shadow/sun, use a tripod in low-light condition.There are no limits about the number of images: but it depends on the complexityof the surface and on the power of the hardware (RAM) which will process thedata.
  27. 27. Archaeological applications: Layers - Example 1In this case 69 pictures were taken with a Sony Cyber-Shot DSC-W90 at 10 MP. … and many others…
  28. 28. Archaeological applications: Layers - Example 1In this case 69 pictures were taken with a Sony Cyber-Shot DSC-W90 at 10 MP. … and many others…In PPT the image were elaborated with In MeshLab the mesh was createdthe feature detector VLFEAT and with with the Poisson surfaceno scaling factor. reconstruction filter (octree depth 10, solver divide 9).
  29. 29. Very good quality of the model and of the details …Isernia La Pineta, Italy (excavation by prof. C. Peretto, University of Ferrara)
  30. 30. … and good texture, very photorealistic.Isernia La Pineta, Italy (excavation by prof. C. Peretto, University of Ferrara)
  31. 31. Archaeological applications: Layers - Example 2In this case 21 pictures were taken with a Sony Cyber-Shot DSC-W90 at 10 MP. … and many others…
  32. 32. Archaeological applications: Layers - Example 2In this case 21 pictures were taken with a Sony Cyber-Shot DSC-W90 at 10 MP. … and many others…In PPT the image were elaborated In MeshLab the mesh was created withwith the feature detector VLFEAT the Poisson surface reconstruction filterand with a scaling factor of 0.75. (octree depth 10, solver divide 9)
  33. 33. Not very good quality of the texture: the color is too flat because of poor lighting, but… Isernia La Pineta, Italy (excavation by prof. C. Peretto, University of Ferrara)
  34. 34. … very good quality of the model and of the details.Isernia La Pineta, Italy (excavation by prof. C. Peretto, University of Ferrara)
  35. 35. … very good quality of the model and of the details.Isernia La Pineta, Italy (excavation by prof. C. Peretto, University of Ferrara)
  36. 36. Archaeological applications: Layers - Example 3In this case 227 pictures were taken with a Apple iPhone 4S at 8 MP. … and many others…
  37. 37. Archaeological applications: Layers - Example 3In this case 227 pictures were taken with a Apple iPhone 4S at 8 MP. … and many others…In PPT the image wereelaborated with thefeature detector VLFEATand with a scaling factorof 0.25.In MeshLab the mesh wascreated with the Poissonsurface reconstructionfilter (octree depth 10,solver divide 9)
  38. 38. The siteIsernia La Pineta, Italy (excavation by prof. C. Peretto, University of Ferrara)
  39. 39. The site Good result of the details(but centimetric precision, not millimetric), but not very good quality of the texture because of poor light Isernia La Pineta, Italy (excavation by prof. C. Peretto, University of Ferrara)
  40. 40. Archaeological applications: UAV Aerial photographyA set of photographs taken with a UAV at different flightaltitude (20 m, 35 m and 50 m) are being developed incollaboration with dr.ssa Paola Piani and Geographikes.r.l. (www.geographike.it) The 3D points cloud The 3D model
  41. 41. ConclusionsThese experiments demonstrated the possibility to document, in three dimensionsand with a very low budget, archaeological sites and finds.Advantages:•fast acquisition and processing•good scalability, both small and huge model can be acquired•non-expert users can create his/her 3D model•cheap•it needs only the equipment which is normally used in an excavation (digitalcamera and total station)•easily portable hardware components allow archaeologists to work under criticalor extreme conditions (e.g. in high mountain, underwater or inside a cave)Disadvantages:•accuracy depends on some factors, in particular the lighting conditions and theperformance of the PC used in the processing•the texture obtained by the points cloud is very good for objects of smalldimensions, but less for the large models
  42. 42. On-line resource opentechne.wordpress.com This is our blog where you can find and read tutorials and case studies about the use of open source applications in archeology and cultural heritage. In the download section is possible to download some of our papers, posters, presentations ... and this presentation is available for download too.References•Gonizzi Barsanti S., Gherdevich D., Degrassi D., 2011. Use Of Low Cost UAV Systems In ArchaeologicalResearch And Disclosure, ISPRS WG V/2 York, UK, Workshop (17 -19 August 2011)www.academia.edu/1122557/USE_OF_LOW_COST_UAV_SYSTEMS_IN_ARCHEAOLOGICAL_RESEARCH_AND_DISCLOSURE•Callieri M., DellUnto N., Dellepiane M., Scopigno R., Soderberg B., Larsson L. 2011. Documentation andInterpretation of an Archeological Excavation: an Experience with Dense Stereo Reconstruction Tools.VAST11: The 12th International Symposium on Virtual Reality, Archaeology and Intelligent CulturalHeritage: 33-40http://vcg.isti.cnr.it/Publications/2011/CDDSSL11/Callieri_etAl_Documenting.pdf•Moulon P., Bezzi A., 2011. Python Photogrammetry Toolbox: una soluzione libera per la documentazionetridimensionale, Archeofoss 2011. Open Source, Free Software e Open Format nei processi di ricercaarcheologica VI Workshop (Napoli, 9/10 giugno 2011)http://imagine.enpc.fr/publications/papers/ARCHEOFOSS.pdf (english version) This work is licensed under the Creative Commons Attribution-Non Commercial–No Derivs 3.0 Unported License.

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