3D structural controls of the shear zone hosted Dugald River zinc-lead-silver deposit, Mount Isa Inlier, Australia

Pieter Creus undertook a detailed 3D structural geological study of the Dugald River Zn-Pb-Ag deposit. In the study he found that the deposit formed during two successive mineralisation events. The mineralisation model is a new style of shear-zone hosted Zinc mineralisation in the region

Fuentes de color mejoradas para el modelado tridimensional de artefactos arqueológicos de tamaño medio localizados in situ.

[EN] The paper describes a color enhanced processing system - applied as case study on an artifact of the Pompeii archaeological area - developed in order to enhance different techniques for reality-based 3D models construction and visualization of archaeological artifacts. This processing allows rendering reflectance properties with perceptual fidelity on a consumer display and presents two main improvements over existing techniques: a. the color definition of the archaeological artifacts; b. the comparison between the range-based and photogrammetry-based pipelines to understand the limits of use and suitability to specific objects.[ES] El documento describe un sistema mejorado de procesamiento de color, aplicado como caso de estudio sobre un artefacto de la zona arqueológica de Pompeya. Este sistema se ha desarrollado con la finalidad de mejorar las diferentes técnicas para la construcción de modelos 3D basados sobre datos de la realidad y para la visualización de artefactos arqueológicos. Este proceso permite visualizar las propiedades de reflectancia con fidelidad perceptible en una pantalla de usuario y presenta dos mejoras principales respecto a las técnicas existentes:a. la definición del color de los artefactos arqueológicos;b. la comparación entre los flujos de trabajo basados en range-based-modeling y en fotogrametría, para entender los límites de uso y la adecuación a los objetos específicos.Apollonio, FI.; Ballabeni, M.; Gaiani, M. (2014). Color enhanced pipelines for reality-based 3D modeling of on site medium sized archeological artifacts. Virtual Archaeology Review. 5(10):59-76. https://doi.org/10.4995/var.2014.4218OJS5976510AGISOFT PHOTOSCAN (2014), http://www.agisoft.ru.ALLEN P., FEINER S., et al. 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(eds), Recording, Modeling and Visualization of Cultural Heritage, Taylor & Francis.BOOCHS F., BENTKOWSKA-KAFEL A., et al. (2013): "Towards optimal spectral and spatial documentation of Cultural Heritage. COSCH - an interdisciplinary action in the COST framework", in ISPRS Arch., Vol. XL-5/W2, 2013, pp. 109-113.CALLIERI M., CIGNONI P., et al. (2008): "Masked photo blending: mapping dense photographic dataset on high-resolution 3D models", in Computer & Graphics, Vol. 32, N. 4, 2008, pp. 464 - 473.CALLIERI M., DELLEPIANE M., et al. (2011): "Processing Sampled 3D Data: Reconstruction and Visualization Technologies", in F. Stanco, S. Battiato, G. Gallo (eds.), Digital Imaging for Cultural Heritage Preservation: Analysis, Restoration and Reconstruction of Ancient Artworks, Taylor and Francis, pp. 105-136.CORSINI M., DELLEPIANE M., et al. 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(2012): "Flow-Based Local Optimization for Image-to-Geometry Projection", in IEEE Transactions on Visualization and Computer Graphics, Vol. 18, N. 3, 2012, pp. 463-474. http://dx.doi.org/10.1109/TVCG.2011.75DELLEPIANE M., DELL'UNTO N., et al. (2013a): "Archeological excavation monitoring using dense stereo matching techniques", in Journal of Cultural Heritage, Vol. 14, N. 3, 2013, pp. 201-210. http://dx.doi.org/10.1016/j.culher.2012.01.011DELLEPIANE M., SCOPIGNO R. (2013b): "Global refinement of image-to-geometry registration for color projection", in DigitalHeritage 2013 Proceedings, 2013, Vol. 1, pp. 39-46.DXO (2014), http://www.dxo.com/intl/photography/dxo-optics-pro/EL-HAKIM S.F., BRENNER C., ROTH G. (1998): "A multi-sensor approach to creating accurate virtual environments", in ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 53, N. 6, pp. 379-391. http://dx.doi.org/10.1016/S0924-2716(98)00021-5EL-HAKIM S.F., BERALDIN J.-A., et al. (2004): "Detailed 3D reconstruction of large-scale heritage sites with integrated techniques", in Computer Graphics and Applications, Vol. 24, N. 3, 2004, pp. 21-29. http://dx.doi.org/10.1109/MCG.2004.1318815EL-HAKIM S.F., BERALDIN J.-A. (2007): "Sensor integration and visualization", in Fryer, Mitchell & Chandler (eds.), Applications of 3D Measurement from Images, Whittles Publishing, pp. 259-298.ENGLISH HERITAGE (2005): Metric Survey Specifications for English Heritage. English Heritage Report.ENGLISH HERITAGE (2011), 3D Laser Scanning for Heritage (second edition), English Heritage Publishing.FURUKAWA Y., PONCE J. (2010): "Accurate, dense, and robust multi-view stereopsis", in IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 32, N. 8, pp. 1362-1376. http://dx.doi.org/10.1109/TPAMI.2009.161GAIANI M., MICOLI L.L. (2005): "A framework to build and visualize 3D models from real world data for historical architecture and archaeology as a base for a 3D information system", in Forte M. (a cura di), The reconstruction of Archaeological Landscapes through Digital Technologies, BAR International series, 1379, pp. 103-125.GAIANI M., ROSSI M., RIZZI A. (2003): "Percezione delle immagini virtuali", in M. Gaiani (ed.), Metodi di Prototipazione Digitale e Visualizzazione per il Disegno Industriale, l'Architettura degli Interni e i Beni Culturali, Polidesign, Milano, 2003.GAIANI M., BENEDETTI B., REMONDINO F. (eds) (2010): Modelli digitali 3D in archeologia: il caso di Pompei, Edizioni della Normale, Pisa, 2010.GAŠPAROVIC M., MALARIC I. (2012): "Increase of readability and accuracy of 3D models using fusion of Close Range Photogrammetry and Laser Scanning", in ISPRS Arch. Photogramm. Remote Sens., Vol. XXXIX-B5, pp. 93-98.GODIN G., BORGEAT L., et al. (2010): "Issues in Acquiring, Processing and Visualizing Large and Detailed 3D Models", in Information Sciences and Systems (CISS), 44th Annual Conference on, pp.1-6. http://dx.doi.org/10.1109/ciss.2010.5464966GONIZZI BARSANTI S., MICOLI L.L., GUIDI G. (2013a): "Quick textured mesh generation for massive 3D digitization of museum artifacts", in DigitalHeritage 2013, Vol. 1, pp. 197-200.GONIZZI BARSANTI S., REMONDINO F., VISINTINI D. (2013b): "3D surveying and modeling of archaeological sites - some critical issues", in ISPRS Ann. Photogramm. Remote Sens., Vol. II-5/W1, 2013, pp. 145-150.GRUSSENMEYER P., LANDES T., et al. (2008): "Comparison methods of terrestrial laser scanning, photogrammetry and tacheometry data for recording of cultural heritage buildings", in ISPRS Arch. Photogramm. Remote Sens., Vol. XXXVII/W5, pp. 213-218.GUARNIERI A., REMONDINO F., VETTORE A. (2006): "Digital photogrammetry and TLS data fusion applied to Cultural Heritage 3D modeling", in ISPRS Arch., Vol. XXXVI/W6, pp. 6.HAPPA J., BASHFORD-ROGERS T., et al. (2012): "Cultural Heritage Predictive Rendering", in Computer Graphics Forum, Vol. 31, N. 6, 2012, pp. 1823-1836. http://dx.doi.org/10.1111/j.1467-8659.2012.02098.xHIRSCHMÜLLER H. (2005): "Accurate and efficient stereo processing by semi-global matching and mututal information", in CVPR 2005 proceedings, Vol. 2, pp. 807-814.HIRSCHMUELLER H. (2008): "Stereo processing by semi- global matching and mutual information", in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30, N. 2, pp. 328-41. http://dx.doi.org/10.1109/TPAMI.2007.1166KARSIDAG G., ALKAN R.M. (2012): "Analysis of The Accuracy of Terrestrial Laser Scanning Measurements", in FIG Working Week 2012 - Knowing to manage the territory, protect the environment, evaluate the cultural heritage proceedings, TS07A - Laser Scanners I, 6097.KAWAKAMI R., IKEUCHI K., TAN R.T. (2005): "Consistent surface color for texturing large objects in outdoor scenes", in ICCV 2005 proceedings, Vol. 2, 2005, pp. 1200-1207.IMATEST (2014), http://www.imatest.com/homeIMAGENOMIC LLC (2012): Noiseware 5 Plug-In User's Guide, 2012INNOVMETRIC POLYWORKS (2014): http://www.innovmetric.com/polyworks/Surveying/LENSCH H.P.A., KAUTZ J., et al. (2003): "Image-based reconstruction of spatial appearance and geometric detail", in ACM Trans. Graph., Vol. 22, N. 2, 2003, pp. 234-257. http://dx.doi.org/10.1145/636886.636891LOWE D. (2004): "Distinctive image features from scale-invariant keypoints", in IJCV, Vol. 60, N. 2, 2004, pp. 91-110.MESHLAB (2014): http://meshlab.sourceforge.net/MUDGE M., SCHROER C., et al. 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Robust signatures for 3D face registration and recognition

PhDBiometric authentication through face recognition has been an active area of research for the last few decades, motivated by its application-driven demand. The popularity of face recognition, compared to other biometric methods, is largely due to its minimum requirement of subject co-operation, relative ease of data capture and similarity to the natural way humans distinguish each other. 3D face recognition has recently received particular interest since three-dimensional face scans eliminate or reduce important limitations of 2D face images, such as illumination changes and pose variations. In fact, three-dimensional face scans are usually captured by scanners through the use of a constant structured-light source, making them invariant to environmental changes in illumination. Moreover, a single 3D scan also captures the entire face structure and allows for accurate pose normalisation. However, one of the biggest challenges that still remain in three-dimensional face scans is the sensitivity to large local deformations due to, for example, facial expressions. Due to the nature of the data, deformations bring about large changes in the 3D geometry of the scan. In addition to this, 3D scans are also characterised by noise and artefacts such as spikes and holes, which are uncommon with 2D images and requires a pre-processing stage that is speci c to the scanner used to capture the data. The aim of this thesis is to devise a face signature that is compact in size and overcomes the above mentioned limitations. We investigate the use of facial regions and landmarks towards a robust and compact face signature, and we study, implement and validate a region-based and a landmark-based face signature. Combinations of regions and landmarks are evaluated for their robustness to pose and expressions, while the matching scheme is evaluated for its robustness to noise and data artefacts

Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning

The importance of landscape and heritage recording and documentation with optical remote sensing sensors is well recognized at international level. The continuous development of new sensors, data capture methodologies and multi-resolution 3D representations, contributes significantly to the digital 3D documentation, mapping, conservation and representation of landscapes and heritages and to the growth of research in this field. This article reviews the actual optical 3D measurement sensors and 3D modeling techniques, with their limitations and potentialities, requirements and specifications. Examples of 3D surveying and modeling of heritage sites and objects are also shown throughout the paper

Digital Multispectral Map Reconstruction Using Aerial Imagery

Advances made in the computer vision field allowed for the establishment of faster and more accurate photogrammetry techniques. Structure from Motion(SfM) is a photogrammetric technique focused on the digital spatial reconstruction of objects based on a sequence of images. The benefit of Unmanned Aerial Vehicle (UAV) platforms allowed the ability to acquire high fidelity imagery intended for environmental mapping. This way, UAV platforms became a heavily adopted method of survey. The combination of SfM and the recent improvements of Unmanned Aerial Vehicle (UAV) platforms granted greater flexibility and applicability, opening a new path for a new remote sensing technique aimed to replace more traditional and laborious approaches often associated with high monetary costs. The continued development of digital reconstruction software and advances in the field of computer processing allowed for a more affordable and higher resolution solution when compared to the traditional methods. The present work proposed a digital reconstruction algorithm based on images taken by a UAV platform inspired by the work made available by the open-source project OpenDroneMap. The aerial images are inserted in the computer vision program and several operations are applied to them, including detection and matching of features, point cloud reconstruction, meshing, and texturing, which results in a final product that represents the surveyed site. Additionally, from the study, it was concluded that an implementation which addresses the processing of thermal images was not integrated in the works of OpenDroneMap. By this point, their work was altered to allow for the reconstruction of thermal maps without sacrificing the resolution of the final model. Standard methods to process thermal images required a larger image footprint (or area of ground capture in a frame), the reason for this is that these types of images lack the presence of invariable features and by increasing the image’s footprint, the number of features present in each frame also rises. However, this method of image capture results in a lower resolution of the final product. The algorithm was developed using open-source libraries. In order to validate the obtained results, this model was compared to data obtained from commercial products, like Pix4D. Furthermore, due to circumstances brought about by the current pandemic, it was not possible to conduct a field study for the comparison and assessment of our results, as such the validation of the models was performed by verifying if the geographic location of the model was performed correctly and by visually assessing the generated maps.Avanços no campo da visão computacional permitiu o desenvolvimento de algoritmos mais eficientes de fotogrametria. Structure from Motion (SfM) é uma técnica de fotogrametria que tem como objetivo a reconstrução digital de objectos no espaço derivados de uma sequência de imagens. A característica importante que os Veículos Aérios não-tripulados (UAV) conseguem fornecer, a nível de mapeamento, é a sua capacidade de obter um conjunto de imagens de alta resolução. Devido a isto, UAV tornaram-se num dos métodos adotados no estudo de topografia. A combinação entre SfM e recentes avanços nos UAV permitiram uma melhor flexibilidade e aplicabilidade, permitindo deste modo desenvolver um novo método de Remote Sensing. Este método pretende substituir técnicas tradicionais, as quais estão associadas a mão-de-obra intensiva e a custos monetários elevados. Avanços contínuos feitos em softwares de reconstrução digital e no poder de processamento resultou em modelos de maior resolução e menos dispendiosos comparando a métodos tradicionais. O presente estudo propõe um algoritmo de reconstrução digital baseado em imagens obtidas através de UAV inspiradas no estudo disponibilizado pela OpenDroneMap. Estas imagens são inseridas no programa de visão computacional, onde várias operações são realizadas, incluindo: deteção e correspondência de caracteristicas, geração da point cloud, meshing e texturação dos quais resulta o produto final que representa o local em estudo. De forma complementar, concluiu-se que o trabalho da OpenDroneMap não incluia um processo de tratamento de imagens térmicas. Desta forma, alterações foram efetuadas que permitissem a criação de mapas térmicos sem sacrificar resolução do produto final, pois métodos típicos para processamento de imagens térmicas requerem uma área de captura maior, devido à falta de características invariantes neste tipo de imagens, o que leva a uma redução de resolução. Desta forma, o programa proposto foi desenvolvido através de bibliotecas open-source e os resultados foram comparados com modelos gerados através de software comerciais. Além do mais, devido à situação pandémica atual, não foi possível efetuar um estudo de campo para validar os modelos obtidos, como tal esta verificação foi feita através da correta localização geográfica do modelo, bem como avaliação visual dos modelos criados

Structure From Motion Methodology Captures Seasonal Influences on Coastal Bluff Erosion and Landslide Hazards in Casco Bay, ME

Shoreline erosion in response to rising sea level is a global problem. Recognizing the need for observational data on coastal bluff recession in Casco Bay, Maine, we employed Structure from Motion (SfM) photogrammetric methods in a dynamic intertidal environment. Evaluating the method as a means to measure and monitor dynamic geomorphological changes occurring at a coastal bluff shows that a spatial resolution of centimeters over an area of 10’s to 100’s of meters can be attained at relatively low cost. The efficient methodology allows for frequent surveys at an operational scale, leading to greater temporal resolution and quantification of bluff erosion activity that supports understanding of the local geohazard. With the greater temporal resolution gained from this evaluation additional inferences are made towards seasonal controls on bluff geomorphology. In the local temperate climate, the dominant erosional actor is characteristically linked to seasonal transitions. Given the urgency of coastal erosion, the lack of local records, and newfound feasibility of repeat surveys, Structure from Motion presents the opportunity to address the uncertainty of bluff instability with an approach that accounts for quantified change over time. Observations were evaluated with respect to: 1) the coastal bluff erosion cycle conceptual model; 2) local landslide hazards; and 3) preservation of a shoreline status record

3D structural characterization of outcrops by means of close-range multi-view stereo-photogrammetry

Image-based 3D modelling is increasingly used as a fast and cheap alternative to laser-scanning for the 3D digital representation of geological outcrops. This rapidly improving technique is progressively opening the way to the widespread use of virtual outcrop models in geology, as the technique allows nearly everybody to construct a detailed digital model of geological exposures simply using a few handy and cheap devices. In this dissertation, the photogrammetry method has been used to demonstrate and evaluate the potential of virtual outcrops in structural geology. In particular, through the analysis of different outcrops at different scales, I showed that virtual outcrop models enable a switch from a mere descriptive/qualitative analysis of the outcrops to a quantitative one. In fact, by mean of virtual reality it is possible to overcome almost all technical limitations that are generally encountered during field work at different scales including prospective distortion, inaccessibility and the lack of instruments for quantitative acquisition of data, among others

Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a divide-and-conquer scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected vertices to produce triangulated mesh models. These triangulated mesh models are suitable for many applications, such as 3D mapping, urban planning and augmented reality

Advancements in multi-view processing for reconstruction, registration and visualization.

The ever-increasing diffusion of digital cameras and the advancements in computer vision, image processing and storage capabilities have lead, in the latest years, to the wide diffusion of digital image collections. A set of digital images is usually referred as a multi-view images set when the pictures cover different views of the same physical object or location. In multi-view datasets, correlations between images are exploited in many different ways to increase our capability to gather enhanced understanding and information on a scene. For example, a collection can be enhanced leveraging on the camera position and orientation, or with information about the 3D structure of the scene. The range of applications of multi-view data is really wide, encompassing diverse fields such as image-based reconstruction, image-based localization, navigation of virtual environments, collective photographic retouching, computational photography, object recognition, etc. For all these reasons, the development of new algorithms to effectively create, process, and visualize this type of data is an active research trend. The thesis will present four different advancements related to different aspects of the multi-view data processing: - Image-based 3D reconstruction: we present a pre-processing algorithm, that is a special color-to-gray conversion. This was developed with the aim to improve the accuracy of image-based reconstruction algorithms. In particular, we show how different dense stereo matching results can be enhanced by application of a domain separation approach that pre-computes a single optimized numerical value for each image location. - Image-based appearance reconstruction: we present a multi-view processing algorithm, this can enhance the quality of the color transfer from multi-view images to a geo-referenced 3D model of a location of interest. The proposed approach computes virtual shadows and allows to automatically segment shadowed regions from the input images preventing to use those pixels in subsequent texture synthesis. - 2D to 3D registration: we present an unsupervised localization and registration system. This system can recognize a site that has been framed in a multi-view data and calibrate it on a pre-existing 3D representation. The system has a very high accuracy and it can validate the result in a completely unsupervised manner. The system accuracy is enough to seamlessly view input images correctly super-imposed on the 3D location of interest. - Visualization: we present PhotoCloud, a real-time client-server system for interactive exploration of high resolution 3D models and up to several thousand photographs aligned over this 3D data. PhotoCloud supports any 3D models that can be rendered in a depth-coherent way and arbitrary multi-view image collections. Moreover, it tolerates 2D-to-2D and 2D-to-3D misalignments, and it provides scalable visualization of generic integrated 2D and 3D datasets by exploiting data duality. A set of effective 3D navigation controls, tightly integrated with innovative thumbnail bars, enhances the user navigation. These advancements have been developed in tourism and cultural heritage application contexts, but they are not limited to these

Machine learning for the automation and optimisation of optical coordinate measurement

Camera based methods for optical coordinate metrology are growing in popularity due to their non-contact probing technique, fast data acquisition time, high point density and high surface coverage. However, these optical approaches are often highly user dependent, have high dependence on accurate system characterisation, and can be slow in processing the raw data acquired during measurement. Machine learning approaches have the potential to remedy the shortcomings of such optical coordinate measurement systems. The aim of this thesis is to remove dependence on the user entirely by enabling full automation and optimisation of optical coordinate measurements for the first time. A novel software pipeline is proposed, built, and evaluated which will enable automated and optimised measurements to be conducted. No such automated and optimised system for performing optical coordinate measurements currently exists. The pipeline can be roughly summarised as follows: intelligent characterisation -> view planning -> object pose estimation -> automated data acquisition -> optimised reconstruction. Several novel methods were developed in order to enable the embodiment of this pipeline. Chapter 4 presents an intelligent camera characterisation (the process of determining a mathematical model of the optical system) is performed using a hybrid approach wherein an EfficientNet convolutional neural network provides sub-pixel corrections to feature locations provided by the popular OpenCV library. The proposed characterisation scheme is shown to robustly refine the characterisation result as quantified by a 50 % reduction in the mean residual magnitude. The camera characterisation is performed before measurements are performed and the results are fed as an input to the pipeline. Chapter 5 presents a novel genetic optimisation approach is presented to create an imaging strategy, ie. the positions from which data should be captured relative to part’s specific geometry. This approach exploits the computer aided design (CAD) data of a given part, ensuring any measurement is optimal given a specific target geometry. This view planning approach is shown to give reconstructions with closer agreement to tactile coordinate measurement machine (CMM) results from 18 images compared to unoptimised measurements using 60 images. This view planning algorithm assumes the part is perfectly placed in the centre of the measurement volume so is first adjusted for an arbitrary placement of the part before being used for data acquistion. Chapter 6 presents a generative model for the creation of surface texture data is presented, allowing the generation of synthetic butt realistic datasets for the training of statistical models. The surface texture generated by the proposed model is shown to be quantitatively representative of real focus variation microscope measurements. The model developed in this chapter is used to produce large synthetic but realistic datasets for the training of further statistical models. Chapter 7 presents an autonomous background removal approach is proposed which removes superfluous data from images captured during a measurement. Using images processed by this algorithm to reconstruct a 3D measurement of an object is shown to be effective in reducing data processing times and improving measurement results. Use the proposed background removal on images before reconstruction are shown to benefit from up to a 41 % reduction in data processing times, a reduction in superfluous background points of up to 98 %, an increase in point density on the object surface of up to 10 %, and an improved agreement with CMM as measured by both a reduction in outliers and reduction in the standard deviation of point to mesh distances of up to 51 microns. The background removal algorithm is used to both improve the final reconstruction and within stereo pose estimation. Finally, in Chapter 8, two methods (one monocular and one stereo) for establishing the initial pose of the part to be measured relative to the measurement volume are presented. This is an important step to enabling automation as it allows the user to place the object at an arbitrary location in the measurement volume and for the pipeline to adjust the imaging strategy to account for this placement, enabling the optimised view plan to be carried out without the need for special part fixturing. It is shown that the monocular method can locate a part to within an average of 13 mm and the stereo method can locate apart to within an average of 0.44 mm as evaluated on 240 test images. Pose estimation is used to provide a correction to the view plan for an arbitrary part placement without the need for specialised fixturing or fiducial marking. This pipeline enables an inexperienced user to place a part anywhere in the measurement volume of a system and, from the part’s associated CAD data, the system will perform an optimal measurement without the need for any user input. Each new method which was developed as part of this pipeline has been validated against real experimental data from current measurement systems and shown to be effective. In future work given in Section 9.1, a possible hardware integration of the methods developed in this thesis is presented. Although the creation of this hardware is beyond the scope of this thesis