modelling 3d scanned data to visualise and analyse the...

Modelling 3D scanned data to visualise and analyse the Built Environment for

regenerationArayici, Y, Hamilton, A and Gamito, P

Title Modelling 3D scanned data to visualise and analyse the Built Environment for regeneration

Authors Arayici, Y, Hamilton, A and Gamito, P

Type Article

URL This version is available at: http://usir.salford.ac.uk/584/

Published Date 2006

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Modelling 3D Scanned Datato Visualise and Analysethe Built Environment for RegenerationYusuf Arayici, Andy Hamilton1 and Pedro Gamito2

ABSTRACT

The renovation and refurbishment market is rapidly expanding in the construction industry. Theregeneration and transformation of cities from the industrial age (unsustainable) to the knowledgeage (sustainable) is essentially a “whole life cycle” process consisting of: planning, development,operation, reuse, and renewal. Advanced digital mapping technologies are enablers for effective e-planning, consultation, and communication of users’ views during the planning, design, construction,and life cycle process of the built environment. Those technologies can be used to enhance productivitygains by promoting a free-flow of information between departments, divisions, offices, and sites, andbetween themselves, their contractors, and partners. Such is the case with the 3D laser scanner,which enables digital documentation of buildings, sites, and physical objects for reconstruction, andrestoration. It also facilitates the creation of educational resources within the built environment, aswell as the reconstruction of the built environment. The use of a 3D scanner in combination with a 3Dprinter provides the transformation of digital data from the captured CAD model back to a physicalmodel in an appropriate scale - reverse prototyping. The use of these technologies act as keyenablers of the creation of new approaches to the “Whole Life Cycle” process within the built andhuman environment for the 21st century. This paper describes the research for building data integrationin the INTELCITIES project undertaken by a European consortium of researchers and practitionersunder the Framework 6 research programme to develop a prototype system for the e-City Platform inorder to pool the advanced knowledge and experiences of electronic government, planning systems,and citizen participation from across Europe (www.intelcitiesproject.com). The scope includes capturingthe digital data of existing buildings using 3D laser scanning equipment and illustrating of howdigitised building data can be integrated with other types of city data, using nD modelling, tosupport integrated intelligent city systems for enhancing the refurbishment process in the built environment.

KEYWORDS

3D Laser ScannerIntelcitiesData IntegrationBuilding ModellingPrototypingObject Recognition

1 School of Construction and Property Management

University of Salford, Greater Manchester, UK

[email protected], [email protected] University LusÓfona de Humanidades e Tecnologias, Lisbon, Portugal

[email protected]

Surveying and Built Environment Vol 17(2), 7-28 December 2006 ISSN 1816-9554

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INTRODUCTION

Cities are transforming themselves from industrialto post-industrial. This regeneration is seen as a“Whole life cycle” process of constructionconsisting of: Planning, Development, Operation,and Reuse. In regards to cultural heritage,intervention within the areas of historical andarchitectural importance, where one findsgroupings of monumental and cultural heritage,is a complex task that implies a greatresponsibility, since inappropriate restoration canresult in irreversible damage (Yamada andTakase, 2004). Therefore, it is fundamental tohave both detailed information and the tools andtechnologies to al low for an ef fect ivemanipulation and operation of data generatedduring the complete life cycle of an historicallandscape.

Virtual 3D models of monuments and structuresthat have largely disappeared offer greatpotential. The use of 3D digitization andmodelling in documenting heritage sites hasincreased significantly over the past few years.This is mainly due to advances in laser scanningtechniques, 3D modelling software; image-basedmodelling techniques, computer power, andvirtual reality (Balletti, et al, 2004), (Arayici andHamilton, 2005). The difficulty in visualising 2Dplans of building elements and componentsbrings about errors in interpreting designspecifications in terms of accuracy, andcompleteness. Besides, accessibility is anothermajor problem encountered by surveyors. Anumber of strategies has been set out to improveefficiency and the quality of design within thebuilt environment. Capturing and modelling the3D information of the built environment is still abig challenge. A number of techniques andtechnologies are now in use. These includeElectronic Distance Measurement (EDM), GlobalPositioning System (GPS) and photogrammetricapplication, and remote sensing applications.However, the 3D laser scanner comes with astronger advantage compared to the aboveapplications, as it is not limited to the surveying

field. A key objective is to develop existingsystems, such as Geographical InformationSystems (GIS), Virtual Reality (VR) tools, anddecision support systems for buildings, and toemploy ci ty planning for use in urbanregeneration and integrating all with the laserscanner to attain the benefits of working in aholistic environment. The new integrated systemwill facilitate a holistic approach to problemsand thus have a much greater functionality thanthe individual sub systems.

In the next section, the 3D laser scanningtechnology, its features, advantages, anddisadvantages will be explained.

3D LASER SCANNERTECHNOLOGYRecently, new instruments were introduced in thefield of surveying that are able to acquire portionsof land and objects of various shapes and sizes.These instruments, based on laser technology,are commonly known as terrestrial laser scanners.While laser scanner instruments based on thetriangulation principle and high degrees ofprecision have been widely used since the1980s, TOF (Time of Flight) instruments havebeen developed for metric survey applicationsonly in the last five years (Bornaz and Rinaudo,

Modelling 3D Scanned Data to Visualise and Analyse the Built Environment for Regeneration

2004, Boehler and Marbs, 2002).

These types of laser scanners can be consideredhighly automated total stations. They are usuallymade up of a laser, which has been optimisedfor high speed surveying, and a set of mechanismsthat allows the laser beam to be directed in spaceat a range that varies according to the instrumentthat is being used. For each acquired point, adistance is measured on a known direction: X, Y,and Z coordinates of a point can be computedfor each recorded distance direction. Laserscanners allow millions of points to be recordedin a few minutes. Because of their practicality andversatility, these kinds of instruments are todaywidely used in the field of architectural,

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archaeological, and environmental surveying(Valanis & Tsakiri, 2004).

This innovation is significant because it has thepotential to solve problems that have always beenassociated with the design and construction ofexisting buildings with reuse goals. For example, itcan provide faster, better quality, and more preciseanalysis and feature detection for building surveys.Besides, in the built environment, the use of the 3Dlaser scanner enables digital documentation ofbuildings, sites, and physical objects forreconstruction and restoration. It also enables thecreation of educational resources within the builtenvironment, including cultural heritage.Furthermore, it can provide reverse engineering inconstruction when existing buildings areredeveloped. Producing building design andComputer Aided Design (CAD) models and VRmodels from an existing building by means of thelaser scanner will facilitate the communicationbetween stakeholders through 3D visualization andfacilitate an analysis of the latest conditions of thebuildings. Besides, it has also the potential toaccurately record inaccessible and potentially

hazardous areas. Consequently, it facilitates “virtualrefurbishment” of buildings and allows the existingstructure and proposed new services to be seen inan effective manner (Ahmed, et al, 2004).

In the research undertaken for the INTELCITIESproject, laser scanner technology wasbrainstormed in a SCRI workshop in October2004, in a Construct IT workshop in November2004, and in three interviews with two architectsfrom Japan and Spain and one building surveyorfrom the UK. The following potential beneficiaries

Table 1: Advantages and disadvantages of 3D laser scanning technology

Advantages

Applicable to all 2D and 3D surfaces

Rapid 3D data collection

Very effective due to large volumes of data collected at a

predictable precision

Ideal for all 3D modelling and visualisation purposes

3D position and surface reflectance generated can be

viewed as an image

Rapidly developing survey technology

Extensive world-wide research and development

currently undertaken

Disadvantages

Some systems do not work in sun or rain

Large 3D data sets require post-processing to produce a

useable output

Difficulty in extracting the edges examples from indistinct

data clouds

Output requires manipulation to achieve acceptable

recording quality

No common data exchange format currently in use

Difficult to stay up-to-date with developments

Hardware expensive and sophisticated software required

to process data

3D Laser Scanning


is described.

As a result, this study has potential benefits andpractical applications to the construction industry.It can provide better support for the evaluation andvisualisation of building maintenance works so thatinformed policies can be effectively targeted. Theseinterviews can be supported by other researchactivities, such as the use of 3D laser scanners tomark the construction schedule and as-built progress(Shih and Wang, 2004). The advantages anddisadvantages of this technology are shown in thetable below (Arayici, et al, 2004).

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Deformation and Sorptivity of Recycled Aggregate Concrete Produced by Two Stage Mixing ApproachModelling 3D Scanned Data to Visualise and Analyse the Built Environment for Regeneration

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INTELCITIES PROJECT

The INTELCITIES (Intelligent Cities) Project is aresearch and development project that aims tohelp achieve the EU policy goal of a knowledgesociety. The INTELCITIES project brings togetherthe combined experience and expertise of keyplayers from across Europe, focusing on e-Government, e-Planning and e-Inclusion, e-LandUse Information Management, e-Regeneration,Integration and Interoperability, Virtual UrbanPlanning, etc. (www.intelcitiesproject.com).

This paper focuses on certain tasks related tothe laser scanner research in the e-Regenerationwork package of the project. These tasks are:

� Building data capture: Captures the digitaldata of existing buildings using 3D laserscanning equipment. Shows how this datacan be used as an information base toenhance the refurbishment process.

� Building data integration: Build the conceptnD modelling system and relate to other datastructures, including relational databases, toillustrate how data can be integrated tosupport intelligent city systems.

In the next section, the research methodology forhow to achieve the above tasks will be explained.Figure 2 illustrates the research methodology ofthe rest of the paper, based on which isconsidered the vision for the use of 3D laserscanners and their integration with various systemsto enhance the refurbishment process.

RESEARCH METHODOLOGY

This section describes the various stagesadopted for the elaboration and evaluationprocess of the building data integration systembased on the research undertaken in theINTELCITIES project. The research strategy is acase study using a prototyping researchapproach. The case studies of the project arethe Jactin House building under refurbishmentin East Manchester and the Peel Building onthe campus of the University of Salford. Thegoal of the research methodology is to describea systematic mechanism to achieve the tasksas cited in the previous section. The evaluationprocess was carried out in four stages, asillustrated in Figure 2. According to the figure,at the first stage, the vision for a conceptualsystem of building data integration is described.The concept covers the integration of laserscanner technology with other technologies andsystems, such as virtual reality (VR), GIS, CAD,the nD modelling database, and so on. At thesecond stage, the integration of the laserscanner technology with CAD systems, VRtoolkits, and 3D printers is further elaboratedon for modelling real world data, such asbuildings, by means of a prototyping technique.At the third stage, the concept of a visualdecision making support system through theintegration of a laser scanner with GIS iselaborated on. Last, the research findings andprogress on integration with nD modellingdatabase are presented, which explains the nDmodelling database, pattern matching, and

1. Describe the Vision for the Conceptual System of Building Data Integration

2. Identify the prototyping approach for real world data modelling for integration with 3D printers and VR

equipment according to the vision

3. Describe the system architecture of a Visual Decision Making Support System for the integration of laser

scanners with GIS

4. Identify the Strategy for the integration with an nD modelling database that is described in the vision


Figure 2: The research methodology that describes the structure of the paper

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Deformation and Sorptivity of Recycled Aggregate Concrete Produced by Two Stage Mixing Approach

object recognition approaches for datamodelling from point cloud data to object-oriented information. This section describes theapproaches adopted for this process.

The Vision of Conceptual System ofBuilding Data Integration

The scope for the conceptual system of building dataintegration in the INTELCITIES project is depicted inFigure 3 below. It includes the integration of laserscanner technology with various systems, such as CADsystems for 2D and 3D CAD plans, and the use ofthe virtual environment tools, such as workbench, aVR projection system, a video conferencing systemfor visualisation and communications, along with a3D printing system for prototyping, a GIS for a visualdecision making support system, and the nD modellingrepository for storing the Industry Foundation Classes(IFC) building information. These are produced witha laser scanning system in a database that embracesinformation in various formats for future use during the

refurbishment process.

The use case diagram in Figure 3 illustrates thebuilding data integration system. The use caseswere used for the conceptual modelling of whatthe system should do from the user’s point of view.It also indicates a number of actors who will beengaged in system. While the implementercaptures the building data and develops VRmodels of the buildings, the developer willintegrate the VR models of the laser scanneddata with various systems to make it ready for avariety of users for building refurbishment andplanning. For example, members of the publiccan visualise the model, and the buildingsurveyor can put the CAD models of the buildingup for refurbishment, while the planning officerand her i tage manager use 3DGIS (3Dimensional GIS) for context and environmentalanalysis and specialist produce physical modelsfrom digital models and IFC data for the nD (nDimensional) modelling database.

Figure 3: Use case diagram for the conceptual modelling


3D Laser Scanning

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According to the use case model above, whenthe concept of a building data integration systemis implemented, a variety of actors can benefitfrom the system. For instance, in regards to culturalheritage, many historical sites are slowlydeteriorating due to exposure to the elements.Although remedial efforts can reduce the rate ofdestruction, a digital model of the site will preserveit indefinitely. Models of historical artefacts alsoallow scientists to study the objects in new ways.For example, archaeologists can measure artefactsin non-contact fashion, which is useful if an objectis fragile. Also, digital models allow objects tobe studied remotely, saving time and travelexpenses and enabling more archaeologists tostudy them. Besides, the heritage manager andplanning officer can utilise the system by usingthe building information captured by means of alaser scanner in the decision making process andverifying the coherence between cultural heritageand city planning interventions. Often thematerials, constructive pathologies, and systemsare insufficient or deficient for archiving and thesharing of information in the documentation ofhistoric buildings, sites, and objects forrefurbishment.

In regards to deformation and inspection,bridges, for example, need to be surveyedperiodically to determine whether significantsettling or other movement has occurred. A 3Dmodel of the site allows engineers to make thesame measurements with the equivalent accuracyin a fraction of the time.

With regards to reverse and rapid prototyping,modelling from reality can be used to reverseengineer real objects, for which a CAD modelmay not be available or has never existed. Theprocess of modelling from reality imports the realworld objects into the computer environment,creating a digital model that can be edited witha CAD program and then creating a physicalmodel of the same object. This will be useful forthe communication between the stakeholders inthe refurbishment process, in particular the clientand architect, and for the publicity of the real

object or building under refurbishment.

Regarding architecture and construction,architects frequently need to determine the “asbuilt” plans of building or other structures, suchas industrial plants, bridges, and tunnels. A 3Dmodel of a site can be used to verify that it wasconstructed according to specifications. Whenpreparing for a renovation or a plant upgrade,the original architectural plans might beinaccurate, if they exist at all. A 3D model allowsan architect to plan a renovation and test outvarious construction options.

In regards to engineering, the process of modellingfrom reality offers an efficient alternative forengineers and surveyors. For example, engineerscan use the information that is converted into IFCin the building life cycle for regeneration.

The following section describes the integrationof laser scanner technology into 3D printer andVirtual Environment tools.

Real world data modelling

The main purpose of the conceptual modeldescribed above is to help one think about realworld problems. The same dimensions ofintegration in the conceptual model can beimplemented by using the BUHU (Research Instituteof Built and Human Environment) equipment.

The spatial data can be obtained by using a3D scanner. By post-processing the capturedspatial data, outputs for different purposes canbe obtained, such as CAD modeling, physicalmodeling by prototyping, and visualization ondifferent platforms. It is depicted in Figure 4.The use of these technologies is a key enabler inthe creation of an integrated system to capture,process, and display 3D information.

For example, these technologies can be usedfor civil engineering and environmental analysis.It permits the user to acquire irregular point cloudsof land areas, rivers, and infrastructure in a fast


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and cheap way. The use of raw laser scannerdata requires orientation and filtering proceduresto generate a 3D model of the surveyed object.It is possible to automatically derive a set ofgeometric information from this 3D model that isuseful for a variety of particular engineering andenvironmental applications, such as dense DigitalTerrain Model (DTM) generation, sections andprofiles, contour maps, volumes, and so on(Bornaz, et al, 2002).

Integration of spatial data can also provide faster,better quality, and more precise analysis andfeature detection for building surveys (Arayici,et al, 2004). One of the major problems thatbuilding surveyors have encountered isinaccessibility. That is to say, on some occasions,they have to measure the details of building andrelevant architectural details on the walls forexample, particularly when developing elevationplans. In these circumstances, building surveyorsare required to estimate the measurements ofthese details, which is very much likely to involve

a variety of errors regarding the accuracy andthe actual design of a building due to a wrongassumption or judgement.

The use of a 3D laser scanner has the potentialto benefit building surveyors and their clients interms of accuracy, speed, and productivity in planpreparation, and then to extend the range ofservices offered through modelling applications.The output of feasibility studies would improveimmeasurably through modelling in areas, suchas those concerning disabled access and firesafety. With current demand for whole lifecosting, asset management planning, anddatabase application, building surveyors arecalled upon to link information in CAD files todatabase files. The possibility of linking thisinformation to 3D models would suggest all sortsof additional benefits. For example, producinga computer model of historical building with 3Dlaser scanner technology can only take a week,and this includes scanning the interior and exteriorof a building in two days and post-processing


Figure 4: Integration of spatial data with 3D printer and the virtual environments

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the point cloud data in three days. For this work,only two people would be required to bothcomplete the initial scans and post-process theraw data. Consequently, this technology issignificantly faster and more effective than anyother surveying application in use. However, thepost-processing part may continue dependingon the end product sought. For example, if it isaimed at rapid prototyping, another two weeksof work will be necessary to complete it.

Rapid PrototypingThe term rapid prototyping refers to a class oftechnologies that automatically construct physicalmodels from Computer Aided Design (CAD)data. These “three dimensional printers” allowdesigners to quickly create tangible prototypesof their designs, rather than just two dimensionalpictures. Such models have numerous uses. Theymake excellent visual aids for communicatingideas with co-workers or clients. In addition,prototypes can be used for design testing. Thereare research activities in rapid prototyping forthe reverse engineering and design of buildingsin particular historic buildings. For example, Alvesand Bartolo (2006) proposed integratedcomputational tools for virtual and physicalautomatic construction using the human visionapproach and 2D photos for 3D computermodelling. However, in this paper rapidprototyping is conducted in accordance with theground-based 3D laser scanner data.

Although several rapid prototyping techniquesexist, all employ the same basic five-step process.These steps are as follows:

1) Create a CAD model of the design: First, theobject to be built is modelled using aComputer Aided Design (CAD) softwarepackage, such as Microstation, which is usedtogether with Polywork point cloud modellerin order to create a CAD model from the laserscanned data of real objects, such as buildings.

First, a model is lined up against the referencefor the coordinate system of Polywork software

and co-planar surfaces with different distancesand depths are defined according to themodel’s facade. Some planes are parallelsto the model and others perpendicular. Next,vertices on the corresponding surfaces areselected and projected to the co-planarsurfaces previously defined. With this processof projection of points onto the co-planarsurfaces, the edges are also defined. Then,the mesh model is optimised to rectify theimperfection in the triangulation that existedin the initial model. Cross-sections are insertedinto the co-planar surfaces to obtain the featurelines of the model. Last, the cross-sections areexported in dxf and then imported intoMicrostation. The result in Microstation is aregular 3D CAD model of the building.

2) Convert the CAD model to STL format:To e s tab l i s h cons i s t ency, t he ST L(Stereolithography) format has been adoptedas the standard of the rapid prototypingindustry. This format represents a three-dimensional surface as an assembly of planartriangles. The STL file contains the coordinatesof the vertices and the direction of the outwardnormal of each triangle. Because STL filesuse planar elements, they cannot representcurved surfaces precisely. Increasing thenumbe r o f t r i ang le s imp roves t heapproximation, but at the cost of bigger filesize. Large, complicated files require moretime to pre-process and build, so a designermust balance accuracy with manageabilityto produce a useful STL file. Since the .stlformat is universal, this process is identical toall of the rapid prototyping techniques.

3) Slice the STL file into thin cross-sectional layers:In the third step, a pre-processing programprepares the STL file to be built. Severalprograms are available, and most allow theuser to adjust the size, location, andorientation of the model. The pre-processingsoftware slices the STL model into a numberof layers from 0.001 mm to 0.07 mm thick,depending on the build technique. The


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program may also generate an auxiliarystructure to support the model during theconstruction. Supports are useful for delicatefeatures, such as overhangs, internalcavities, and thin-walled sections.

4) Construct the model one layer on top another:The fourth step is the actual constructiono f t he pa r t . Us ing one o f seve ra ltechniques, rapid prototyping machinesbuild one layer at a time from polymers orpowdered metal.

5) Clean and finish the model: The final step is post-processing. This involves removing the prototypefrom the machine and detaching any supports.Some photosensitive materials need to be fullycured before use. Prototypes may also requireminor cleaning and surface treatment.

Figures 5 to 10 show the Jactin House example,which is the case study building in EastManchester, for VR models produced from thebuilding data captured by the 3D Laser scannerand CAD models extracted from the VR models.

Figure 5: 12 scans were conducted around Jactin house; the picture below is one of the scans

Figure 6: The individual scans are processed to create the VR model below


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Figure 7: Using co-planar surfaces and creating sharp edges from curves in the model in Figure6, the CAD model below is developed using Polyworks modeller and Microstationsoftware

Figure 8: Polygonal models for printing can be generated from the CAD model above

Figure 9: The images below are samples of the Jactin House model


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The sequence of figures from Figure 5 to Figure10 also illustrates the process of data from realworld to digital modelling and to physicalmodelling, which is one of the dimensions ofintegration between the laser scanner and the3D printer depicted in the conceptual model ofbuilding data integration system in Figure 3.

As illustrated in Figure 4, the system can collectdata from the real world and manipulate it forintegration. For example; the geometric informationcan be obtained using a 3D scanner. By editingand integrating the data, a model of the object(building/urban area) could be created to be usedin the decision-making process. The model can bepresented in different ways, for example, as aphysical model or VR projection system for reverseand forward prototyping, which is shown in Figures5, 6, 7, 8, and 9. An example of visualization inthe VR projection system is illustrated in Figure 10.

This implementation depicted in Figure 10 is thedimension of integration of the laser scanner withthe VR environment tools shown in the conceptmodel of building data integration system inFigures 3 and 4.

In the next section, another dimension of theintegration of a laser scanner with GIS will bediscussed for a Visual Decision Making SupportSystem in regeneration.

An Approach for a Visual DecisionMaking Support System

The aim of this section is to describe a frameworkthat includes a geospatial database, such as thenD modelling database, the 3D laser scanner,and a series of analytical tools that will enablevarious stakeholders in the regeneration processto make decisions relating to building maintenanceworks (Ahmed, et al, 2004). This framework isdepicted in Figure 12, and includes:

1) The development and population of a geo-spatial project database with the digital dataof existing buildings captured with laserscanning equipment.

2) The analysis of complex building informationmaintenance options within a knowledgerepository environment, in which digitalbuilding data that was captured by the laser

Figure 10: Peel building data captured by the laser scanner is textured and presented


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scanner is retrieved with a 3D GIS system forthe analysis.

3) The visualisation of project information througha range of different interconnected graphicwindows. The laser scanner VR model canbe visualised on different platforms.

The geospatial database describes thegeometries of both the building frame and itscomponents. Simple open geometric descriptionsare used, but each entry will also be associatedwith the data on inventory information, such asname, supplier, date installed, replaced, numberof replacements, etc (Ahmed, et al, 2004).

The system will enable the capture of geo-spatialdata using a laser scanner. This data will beprocessed and building frame and componentswill be determined in a CAD environment.Inventory information relating to each frame andcomponent will also be captured within therelational structure of the database. Suchinformation will be accessible in real-time with

some of the attributes (e.g. component supplierinformation) made available through thecommunication layer.

GIS software will be used to generate andanalyse thematic developments relating to thebuilding properties and associated refurbishmentmanagement strategies. Such software willretrieve the building information from thedatabase through the communications layer,which provides users situated in various locationswith access to the database.

The VR environment will be created in a VirtualReality Modelling Language (VRML) interface.The systems are developed based on the sharingof construction information via a central objectorientated project database. Typically, the CADapplication allows a user to create andmanipulate the components of a facility. Thecomponents are stored as instances of classesin an object-oriented database. These instancesare read by the VRML interface in order to createa 3D view of the facility, which gives the user a

Figure 11: Structure of a visual decision making support system


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bet ter environment for navigat ion andwalkthrough. Therefore, the results of the spatialanalysis obtained within the 3-D GIS environmentcan be evaluated in real-time with the options ofviewing building refurbishment alternatives(Mahdjoubi and Ahmed, 2004).

In the next section, the research methodologyfor the actual development and implementationof the conceptual system of building dataintegration will be described.

Integration with the nD modellingRepository

The building data captured by the laser scanneris processed to generate information that will bestored in the nD modelling database in IFCs(Industry Foundation Classes). The informationstored in the database will be available for thedecision making process and be reused in therefurbishment process in the future. To makeprogress in modelling, conversion issues of 3Dscanned data need to be solved. There are certainbarriers related to laser scanner data. For example,there are no standard formats for the distributionof scanned data. This leads to issues relating tocompatibility, the exchange of information, anddata archiving. These barriers can be overcomethrough data conversion from scanned data tostandard data formats such as IFC (IFC2x2,2005). Once this conversion is achieved, it istime to store this information characterised by IFCschema in the nD modelling database.

In this section, the integration concept with thenD modelling database will be elaborated on.The nD modelling database is a multi-dimensionaldata storey to keep information for varioussystems in the building life cycle. The aim of thedatabase development is to design, build, andevaluate the components of an interactive virtualurban planning environment as part of the e-City platform. The nD modelling database is thebase of this interactive virtual urban planningenvironment (Hamilton, et al, 2005).

Figure 12 shows the n-dimensional conceptualurban data model. Entities such as ‘road, railway,pollution, and IFC Building’ have beendescribed. The core of the conceptual datamodel is the abstract entity of ‘administrativeboundary’. An administrative boundary isdefined as the limit of responsibility area. A‘country’ could be the largest administrative area.Countries are composed of counties, cities,districts, and parcels. A parcel can also bedivided into smaller units called ‘partitionparcels’. The attributes of the administrativeboundary are all inherited by these sub classes.The ‘administrative boundary’ classes, such ascountries, counties, cities, districts, and parcels,have relations with geographical entities, suchas roads, railways, water elements, heritageelements, etc. A parcel may have a building onit. IFCs were used to model the building relateddata. An administrative boundary may alsoattract crime and pollution. A city, a parcel, ora user-defined boundary unit may be selectedfor the air, noise pollution simulations (Tanyer, etal, 2005a, 2005b).


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Figure 12: Conceptual urban data model (Source: Tanyer, et al, 2005)


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From 3D Scanned Data to nD Modelled DataThe research to date about object recognitionfrom the laser scanned data has focused on apattern matching approach. Pattern Matchingaddresses issues of searching and matchingstrings and more complicated patterns, such astrees, regular expressions, graphs, point sets, andarrays (Johnson, 2002). The diagram belowshows the pattern matching approach in theINTELCITIES project for object recognition fromthe laser scanned data.

3D CAD models using semi-automatedtechniques were extracted from the polygonalmesh model developed in the laser scannersystem. The extracted CAD model is presentablein any commercial CAD software. According toFigure 13, the pattern matching interface beingdesigned will invoke the 3D CAD model to itsdisplay screen. Highlighting any building framein the model will enable the pattern matcher todefine geometric features as criteria for matching

processes such as shape, sides, width, height,thickness, line type, line thickness, line colour,and so on. Besides the automatic featurerecognition, users can also input further criteriainto the matching process. However, this processis being completed manually in MicrostationTriforma for now because the pattern matchingalgorithm definition is still under investigation.The IFC building model of Jactin House ispresented in Figure 14.

Microstation triforma employs a single buildingmodel concept. All information about a buildingis recorded in a 3D model. Traditionally, a givendoor in a building would be drawn in at leastthree or four places (plan, building elevation,building section, interior elevation, etc). In thesingle building model, it is constructed once andthese various drawings are later extractedautomatically. The single building model requiresbuilding objects, which are defined, edited, andstored in the triforma library.

Figure 13: Data Conversion approach for laser scanned building data

Produces 3D CAD

Search, match, and retrieve

object attributes in the library

Save and store

the model in the IFC data model

Laser scanner

system

Triforma

Object Library

nD Modelling

database

3D CAD

Model

Pattern matching

interface

Object-Oriented

CAD Model

Invoke the

Assign the object attributes to the 3D

CAD Model


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The pattern matcher will access the triformalibrary with the criteria to do “search and match”.Two different types of matching can be done: 1)the exact pattern matching, and 2) theapproximate pattern matching. Exact patternmatching consists of finding the exact pattern. Inthe case of approximate pattern matching, it isa generalisation of the pattern sought and adetermined number of differences between thepattern sought and the objects found in the libraryis allowed.

There will be three types of pattern form: simple,constrained, and variable. All three forms canbe accommodated by the pattern matcherinterface. However, the pattern matcher willhandle them differently to improve efficiency.Simple patterns are simple matches on values.The pattern describes which values must beincluded in the search. For example, the patternmatcher tries to match an instance of a square(a frame) and it finds square-1, square-2, square-3, and square-4, which are all the squares inthe example database.

In case of a constrained pattern form, it is possibleto specify a constraint on a value instead of aspecific value. To do so, a function to beprovided will test the constraint. For example,

the pattern matcher matches the frame to triangle-1, triangle-2, triangle-3, and triangle-4. Theconstraint (value <4) limits the value of sides toless than 4.

In respect to variable types of pattern form,patterns may also include variable references.Variables in patterns can be used to relate values.The first occurrence of a variable in a patterncauses the value in a frame to be bound to thatvariable. The second occurrence forces aconstraint that the value will be equal to the valuebound to the variable. For example, pattern(width a, height a) describes objects with widthsequal to their heights.

Variables may also be used in constraints to relatevalues through more complex relations thansimple equality. For example, pattern (width a,height {value >a}) describes objects with heightsgreater than width. Variables may also be usedto relate values across patterns. Since eachpattern refers to values in a single frame, relatingvalues across frames requires multiple patterns(Yates, 2004). The function, multiple-patternmatch, searches for frames that match a set ofrelated patterns. The multiple-pattern match returnsa list of sub-lists in which the sub-lists contain thevalue of the variables followed by the frames

Figure 14: The building details are defined as triforma objects


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that match each pattern within the set. Thevariables can also be related across frames withconstraints. For example, pattern (width a,height {value >a}, sides 4) describes all objectswith heights greater than the width and with 4sides.

As a result of various matching processes, objectrecognition can be worked out for the interestedbuilding frames in the 3D CAD model. Attributesof the objects matched in the library will be assignedto the building frame in the CAD model, whichresult in the building frames to be defined as buildingobjects. Subsequently, an object-oriented (OO)CAD model will be obtained. This OO CAD modelwill be mapped into IFC schema to be saved andstored in the nD modelling database.

The Object Recognition ApproachTo progress in the area of modelling, conversionissues of 3D scanned data need to be solved.The general problems of 3D data integrationin the built environment were considered byWang and Hamilton (2005). This sectionspecifically addresses the problem of objectrecognition. This is important in realizing thevisualization of 3D models of the buil tenvironment because visualization will beundertaken with the real characteristics andfeatures of real world objects, as opposed toraw 3D models of laser scanned data, whichis difficult to handle for many visualizationsoftware applications due to large file sizes.As a result, data modelling and analysis of laserscanned data can also be done more effectivelyand precisely. This also facilitates the use ofCAD and GIS software, which will not normallysupport raw scanned 3D models.

There are certain barriers. For example, thereare no standard formats for the distribution ofscanned data. This leads to issues relating tocompatibility, the exchange of information, anddata archiving. These barriers can be overcomethrough data conversion from scanned data toa standard data format, such as IFC (IAI, 2004)or IFG (Industry Foundation Classes for GIS).

IFC is an international data standard model forinformation sharing and interoperability in theconstruction industry. On the other hand, IFGalso makes it possible to communicate relevantintel l igent information from various GISstandards to CAD systems using IFC (Wangand Hamilton, 2005).

In the INTELCITIES research programme, wehave an approach for object recognition throughthe simultaneous recognition of multiple objectsin the scenes of polygonal mesh modelsproduced from the laser scanner point clouddata, which contains clutter and occlusion.Recognition is based on matching surfaces bymatching points using spin image representation.Spin imaging is a data level descriptor that isused to match surfaces represented as a surfacemesh (Johnson and Hebert, 1999). Figure 15below describing the process of objectrecognition from the laser scan data wasdeveloped based on a spin image definition fromJohnson and Hebert (1998, 1999).

Through surface matching, an object can beidentified in a scene of laser scanned data bycomparing a targeted surface to an objectsurface stored in a database. When the objectsurface is matched, an interrelation can beestablished between something known (theobject) and something unknown (the scene oflaser scanned data). As a result, informationabout the world is acquired.

Surface matching is based on matchingindividual surface points in order to matchcomplete surfaces (Johnson and Hebert, 1999).By matching points, the problem of surfacematching is broken down into many smallerlocalized problems of point matching. As aresult, matching points provides a method forhandling clutter and occlusion in surfacematching without first segmenting the scene.Clutter points on one surface will not havematching points on the other, and occludedpoints on one surface will not be sought on theother (Ullman, et al, 2002).


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Figure 15: Object recognition from the laser scanner system

VR model of

a building

API (does object

recognition

Object

database

Match the scene spin image

with the object spin images

Assign the objects from object

spin images to the corresponding

elements in the scene spin image

Write the recognised

objects into IFG schema

Write the recognised

object into IFC schema

nD modelling database

Store the data in

the database

Store the data in

the database

To differentiate among points, 2D imagesassociated with each point were constructed.Oriented points, which are 3D points withassociated directions, were used to create spinimages. An oriented point was defined at asurface mesh vertex using the 3D position of thevertex and surface normal at the vertex. Thesurface normal at a vertex was computed byfitting a plane to the points connected to thevertex by the edges at the surface mesh (Johnsonand Hebert, 1998, 1999).

According to Figure 15, the polygonal modelmesh was invoked by the API (ApplicationProgramming Interface) to be developed inorder to create a scene spin image based on aselected scene oriented point. At the same time,the system will access the object database tocreate spin images for each object model inthe database, and these spin images are storedin a spin image stack. Point correspondences

were then established between the selectedpoint and the points with the best matching spinimages on the other surface. This procedurewas repeated for many points until there werea sizeable number of set point correspondences.The point correspondences were then groupedand the outliers eliminated using geometricconsistency.

This surface matching can be extended to objectrecognition as follows. Each object in the objectdatabase is represented by a polygonal mesh.Before recognition, the spin images for allvertices on all models were created and stored.At recognition time, a scene point was selectedand its spin image was generated. Next, itsspin image was correlated with all the spinimages from all the objects. The best matchingmodel spin image will indicate both the bestmatching model and model ver tex aftermatching many scene spin images to model

Produce scene

spin image

Produce scene

spin image


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spin images. The result was a simultaneousrecognition and localization of the objects thatexisted in the scene (Stein and Hebert, 2005).

The following step is to assign and populateobjects to the corresponding elements in thescene of the laser scanner VR mesh model. Inthe end, a new VR model is an object-populatedmesh model. The following step is to write theseobjects at the scene into the IFC schema atbuilding scale or IFG schema at city scale (Wangand Hamilton, 2005). IFC-enabled CADsoftware assists professionals when they plan abuilding or an area with buildings by supplyingan attribute information type of window, costand performance, directly connected to the 3Dmodel. For larger scale integrated data, it isalso necessary to extract parts of the site andbuilding information (in IFC form) and make itavailable in GIS standards.

The information characterised by either the IFCschema or IFG schema will be stored in the nDmodelling (Lee at al, 2003) database. The nDmodelling database is a multi-dimensional datastorey for keeping information for various systemsat the building scale and urban scale. This is anongoing progress, and the focus of future workwill be on the algorithm definition of objectrecognition for data conversion from scanneddata to nD modelled data.

CONCLUSION

This paper explained the research on the use oflaser scanner technology for the bui l tenvironment. The focus was on e-regenerationto facilitate the building refurbishment process.Therefore, building data captured by laserscanners and building data integration withvarious systems were addressed.

In the paper, the INTELCITIES research projectwas introduced. Their scope for the use of thelaser scanner technology for the built environmentat the building scale and urban scale was

described. The research undertaken in the projectfor 3D laser scanner technology mainly focusedon data capture, modelling, and integration.Case studies of Jactin House and the PeelBuilding were given as examples for CAD andVR modelling and integration with othertechnologies, such as the 3D printer and VRprojection system. Furthermore, the potentialbenefits of using a 3D laser scanner wereaddressed. Last, an approach to objectrecognition for object-oriented data modellingfrom the 3D scanned data was discussed. Thebenefits of this approach were noted. Forexample, providing information in standardformats, such as IFC and IFG on the builtenvironment using the laser scanner throughobject recognition approach, will enable oneto communicate with other city and buildingsystems, including CAD and GIS systems.

Generally speaking, the present use of laserscanners in the built environment was criticisedas being too laborious and time consuming.However, the approaches explained in thispaper can lead to answers for overcoming theseissues, and it is envisaged that when the dataconversion problems are solved according tothe methods explained in this paper, the use oflaser scanner VR models can be developedquickly, which will make it feasible for intelligentvisualizations to be produced for a wide rangeof applications.

REFERENCES

Ahmed V, Arayici Y, Hamilton A and Aouad G(2004), Vir tual Bui lding Maintenance:Enhancing Building Maintenance Using 3D-GISand 3D Laser Scanner (VR) Technology,Proceeding of European Conference on Productand Process Modelling in the Building andConstruction Industry (ECPPM), 8-10 September2004, Istanbul, Turkey, 29-34.

Alves NM and Bartolo PJ (2006), Integratedcomputational tools for virtual and physical


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automatic construction, Journal of Automation inConstruction, 15:3, 257-271.

Arayici Y and Hamilton A (2005), Modelling3D Scanned Data to Visualise the Buil tEnvironment, Proceedings of 9th InternationalConference on Information Visualisation, IEEEComputer Society, 6-8 July 2005, London,509-514.

Arayici Y, Hamilton A, Gamito P and AlbergariaG (2004), The Scope in the INTELCITIES Projectfor the Use of the 3D Laser Scanner, Proceedingof ECT2004: The Four th In ternat ionalConference on Engineering ComputationalTechnology, 7-9 September 2004, Lisbon,Portugal.

Balletti C, Guerra F, Vernier P, Studnicka N,Riegl J and Orlandini S (2004), PracticalComparative Evaluation of An Integrated HybridSensor Based On Photogrammetry and LaserScanning for Architectural Representation, XXthISPRS Congress, 12-23 July 2004 Istanbul,Turkey, 536-541.

Boehler W and Marbs A (2002), 3D ScanningInstruments, Proceeding of the CIPA WG 6International Workshop on Scanning For CulturalHeritage Recording, 1-2 September 2002,Corfu, Greece.

Bornaz L, Lingua A and Rinaudo F (2002),Engineering and environmental applications oflaser scanner techniques, International Archivesof Photogrammetry and Remote Sensing. ISSN:1682-1777. Volume XXXIV part 3A+BCD-ROM.

Bornaz L and Rinaudo F (2004), Terrestrial LaserScanning Data Processing, XXth ISPRSCongress, 12-23 July 2004, Istanbul, Turkey,514-520.

Hamilton A, Wang H, Tanyer AM, Arayici Y,Zhang X and Song Y (2005), Urban informationmodel for city planning, ITcon, 10:6, 55-67.

IAI (2002), In ternat ional Al l iance forInteroperability, Available online at: http://www.iaiinternational.org, (accessed 20 June2005).

IFC2X2 (2005), IFC2x Edition 2 Addendum 1,Available online at: http://www.iaiinternational.org/iai_international/Technical_Documents/R2x2_add1/index.html, (accessed 20 June2005).

Johnson AE, and Hebert M (1998), SurfaceMatching for Object Recognition in ComplexThree-Dimensional Scenes, Image and VisionComputing, 16, 635-651.

Johnson AE and Hebert M (1999), Using SpinImages for Efficient Object Recognition inCluttered 3D Scenes, IEEE Transaction on PatternAnalysis and Machine Intelligence, 21:5, 433-449.

Johnson M (2002), A simple pattern matchingalgorithm for recovering empty notes and theirantecedents, Proceeding of 40th Annual Meetingof the Association for Computational Linguistics(ACL), July 2002, Philadelphia, 136-143.

Lee A, Marshall-Ponting AJ, Aouad G, Wu S,Koh WWI, Fu C, Cooper R, Betts M, KagioglouM and Fisher M (2003), Developing a vision ofnD-enabled construction, Construct IT, Universityof Salford, UK.

Lichti D (2004), A Resolution Measure For TerrestrialLaser Scanners, XXth ISPRS Congress, 12-23 July2004 Istanbul, Turkey.

Mahdjoubi L, and Ahmed V (2004), VirtualBuilding Maintenance: Enhancing BuildingMaintenance using 3D GIS and Virtual Reality(VR) Technology’ , Conference of Designing,Managing, and Supporting Construction Projectst h rough I nnova t ion and I T so l u t i on s(INCITE2004), February 2004, Langkawi,Malaysia.


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Stein A and Hebert M (2005), IncorporatingBackground invariance into Feature-BasedObject Recognition, 7th IEEE Workshop onApplication of Computer Vision, January 2005.

Shih NJ and Wang PH (2004), Point-Cloud-Based Comparison between ConstructionSchedule and As-Built Progress: Long-RangeThree-Dimensional Laser Scanner's Approach,Journal of Architectural Engineering, 10:3, 98-102.

Tanyer AM, Tah JHM and Aouad G (2005a),An Integrated Database to Support CollaborativeUrban Planning: The N-Dimensional ModellingApproach, ASCE Conference on Computing inCivil Engineering, 12-15 July 2005, Cancun,Mexico.

Tanyer AM, Tah JHM and Aouad G (2005b),Towards n-Dimensional Modelling in UrbanP lann ing, Innova t ion in Arch i tec tu re ,Engineering & Construction (AEC), 15-17 June2005, Rotterdam, 503-512.

Ullman S, Vidal-Naguet M and Sali E (2002),Visual features of intermediate complexity andtheir use in classification, Nature Neuroscience,5:7, 682-687.

Wang H and Hamilton A (2005), Dataintegration issues within nD Information Modellingfor Urban P lanning, 5th In ternat ionalPostgraduate Research Conference, Salford, UK,194-203.

Yamada O and Takase Y (2004), A Case StudyFor the Practical Use of 3D Digital Archive ofCultural Properties, XXth ISPRS Congress, July2004, Istanbul, Turkey, 12-23.

Yates BR (2004), A Fast Set Intersection AlgorithmFor Sor ted Sequences, Proceeding ofCombinatorial Pattern Matching conference(CPM), July 2004, Istanbul.
