Real world modelling through high resolution digital 3D imaging of objects and structures

Beraldin, J.-A.; Blais, François; Boulanger, Pierre; Cournoyer, Luc; Domey, J.; El-Hakim, Sabry F.; Godin, Guy; Rioux, Marc; Taylor, John

doi:10.1016/s0924-2716(00)00013-7

Cited by 49 publications

(33 citation statements)

References 9 publications

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“…La plupart des projets inalisés ou en cours concernent l'analyse des architectures (Gillings, 2000), des peintures et gravures rupestres (Simpson et al, 2004), des objets et collections des musées (Beraldin et al, 2000) ou encore des structures archéologiques en cours de fouille (Doneus et al, 2011). D'autres perspectives récentes ont intégré ce type de démarche aux analyses de l'érosion des sites (López-Romero et al, 2014).…”

Section: Un Regard Nouveau : Restitution Par L'image De La Fouille Deunclassified

Le tumulus de Kervingar (Plouarzel, Finistère) : un regard nouveau sur les débuts de la recherche archéologique d’après-guerre en Bretagne

Lopez-Romero¹,

Daire²,

Mañana-Borrazás³

et al. 2015

rao

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Le tumulus de Kervingar (Plouarzel, Finistère) : un regard nouveau sur les débuts de la recherche archéologique d'après-guerre en BretagneThe Kervingar tumulus (Plouarzel, Finistère) 'Ouest, 32, 2015, p. 113-128. Résumé : À partir d'une série de documents inédits, ce travail revient sur la fouille de 1953 du tumulus de l'âge du Bronze ancien de Kervingar (Plouarzel, Finistère) par Pierre-Roland Giot (1919-2002. La révision de ces documents et la discussion du contexte de l'époque nous permettent de replacer cette fouille comme l'une des pièces clés du renouveau scientiique qui s'opérera au sein de l'archéologie française dès la in des années 1940. Elle constitue par ailleurs et avant tout l'un des travaux fondamentaux pour comprendre la pensée scientiique qui mènera à la création du « Laboratoire d'Anthropologie, Préhistoire, Protohistoire et Quaternaire armoricains » et qui marquera par la suite une grande partie de la recherche archéologique de l'Ouest de la France durant toute la seconde moitié du xx e siècle. L'existence d'un ilm inédit sur les travaux nous ofre également l'occasion de proposer une méthodologie novatrice d'analyse d'image, avec restitution tridimensionnelle numérique d'une partie de la fouille. Cette perspective ouvre une nouvelle voie dans l'exploitation scientiique des archives anciennes. Pierre-Roland Giot (1919-2002 Abstract: Drawing from a set of unpublished material, this paper revisits the 1953 excavation of the Early Bronze Age mound of Kervingar in Plouarzel (Finistère) by

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Section: Un Regard Nouveau : Restitution Par L'image De La Fouille Deunclassified

Le tumulus de Kervingar (Plouarzel, Finistère) : un regard nouveau sur les débuts de la recherche archéologique d’après-guerre en Bretagne

Lopez-Romero¹,

Daire²,

Mañana-Borrazás³

et al. 2015

rao

View full text Add to dashboard Cite

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“…Meanwhile, like most of surveying devices, TLS need to be calibrated periodically (Santala, J., 2010). TLS has become popular in the 1990s for mobile robot navigation (Singh, S., 1991), in the construction of metric scale 3D models, such as sculptures (Beraldin, J.A., 2000) and industrial applications (Sequeira, V., 2003). There are three types of laser scanner systems based on principles of (i) Time of Flight (TOF) (ii) Triangulation (iii) and Phase Shift measurement system (Anne Chung Wei Lin., 2009).…”

Section: Terrestrial Laser Scanningmentioning

confidence: 99%

Evaluation of Partially Overlapping 3D Point Cloud's Registration by using ICP variant and CloudCompare.

Rajendra¹,

Mehrotra²,

Kale³

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Terrestrial Laser Scanners (TLS) are used to get dense point samples of large object's surface. TLS is new and efficient method to digitize large object or scene. The collected point samples come into different formats and coordinates. Different scans are required to scan large object such as heritage site. Point cloud registration is considered as important task to bring different scans into whole 3D model in one coordinate system. Point clouds can be registered by using one of the three ways or combination of them, Target based, feature extraction, point cloud based. For the present study we have gone through Point Cloud Based registration approach. We have collected partially overlapped 3D Point Cloud data of Department of Computer Science & IT (DCSIT) building located in Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. To get the complete point cloud information of the building we have taken 12 scans, 4 scans for exterior and 8 scans for interior façade data collection. There are various algorithms available in literature, but Iterative Closest Point (ICP) is most dominant algorithms. The various researchers have developed variants of ICP for better registration process. The ICP point cloud registration algorithm is based on the search of pairs of nearest points in a two adjacent scans and calculates the transformation parameters between them, it provides advantage that no artificial target is required for registration process. We studied and implemented three variants Brute Force, KDTree, Partial Matching of ICP algorithm in MATLAB. The result shows that the implemented version of ICP algorithm with its variants gives better result with speed and accuracy of registration as compared with CloudCompare Open Source software.

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“…There are a few references that describe modeling of point clouds obtained from large scale scans, such as buildings and statuary. The following references give some of those details: Beraldin et al [6], Huber et al [41], Pollefeys et al [72], Kanamaru et al [49], El-Hakim [21].…”

Section: Object Identificationmentioning

confidence: 99%

“…-bb*object(obj).S.z -cc*object(obj).T.z; object(obj).corner(5).x = object(obj).Q.x -aa*object(obj).R.x... + bb*object(obj).S.x + cc*object(obj).T.x; object(obj).corner(5).y = object(obj).Q.y -aa*object(obj).R.y... + bb*object(obj).S.y + cc*object(obj).T.y; object(obj).corner(5).z = object(obj).Q.z -aa*object(obj).R.z... + bb*object(obj).S.z + cc*object(obj).T.z; object(obj).corner(6).x = object(obj).Q.x -aa*object(obj).R.x... + bb*object(obj).S.x -cc*object(obj).T.x; object(obj).corner (6).y = object(obj).Q.y -aa*object(obj).R.y... + bb*object(obj).S.y -cc*object(obj).T.y; object(obj).corner (6).z = object(obj).Q.z -aa*object(obj).R.z... + bb*object(obj).S.z -cc*object(obj).T.z; object(obj).corner(7).x = object(obj).Q.x -aa*object(obj).R.x...…”

Section: A11 Object Identification By Binning Scriptsmentioning

confidence: 99%

Construction object identification from LADAR scans:

Gilsinn¹,

Witzgall²,

Cheok³

et al. 2005

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Laser Scanning devices (a.k.a. LADAR for Laser Detection and Ranging) are primarily used in construction projects to capture as-built data for documentation and re-engineering. These systems can rapidly generate unstructured point clouds of scene data within the field of view and line-of-sight of the LADAR. The Construction Metrology and Automation Group (CMAG) at NIST is interested in using these high-resolution scanned data to identify and locate construction objects of interest. The test operation is large-scale pick-and-place of structural steel, where the data from the scans are used to identify the general pose, position and orientation of a target object for initial positioning of a robotic crane. Close-in control of the crane using high framerate flash LADAR is a separate but related area of CMAG research.This initial study describes an experiment in which an I-beam on a concrete floor surface is scanned, and the resulting point cloud data are used to calculate its pose. Multiple scans of two sizes of I-beams were taken with the I-beam placed at various angles relative to the scanner. Two approaches for segmenting potential target objects are described: binning and triangular irregular networks (TINs). Using the method of principal components analysis, the pose of potential target objects is determined. Bounding boxes are then formed around these objects and compared to an ideal bounding box generated from the known geometric specifications of the Ibeam of interest. A measure of best fit is used to determine which scanned object most closely fits the bounding box of the ideal I-beam. A separate laser-based site measurement system (SMS) was used to measure points on the I-beams to form reference data for estimating the closeness of fit of computed pose of the I-beam to measured pose of the I-beam. Three spheres were located in the scan field as a means of registering the scan and SMS axes to one another.

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Real world modelling through high resolution digital 3D imaging of objects and structures

Cited by 49 publications

References 9 publications

Le tumulus de Kervingar (Plouarzel, Finistère) : un regard nouveau sur les débuts de la recherche archéologique d’après-guerre en Bretagne

Le tumulus de Kervingar (Plouarzel, Finistère) : un regard nouveau sur les débuts de la recherche archéologique d’après-guerre en Bretagne

Evaluation of Partially Overlapping 3D Point Cloud's Registration by using ICP variant and CloudCompare.

Construction object identification from LADAR scans:

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