Evaluation of modern camera calibration techniques for conventional diagnostic X-ray imaging settings

[EN] We explore three different alternatives for obtaining intrinsic and extrinsic parameters in conventional diagnostic X-ray frameworks: the direct linear transform (DLT), the Zhang method, and the Tsai approach. We analyze and describe the computational, operational, and mathematical background differences for these algorithms when they are applied to ordinary radiograph acquisition. For our study, we developed an initial 3D calibration frame with tin cross-shaped fiducials at specific locations. The three studied methods enable the derivation of projection matrices from 3D to 2D point correlations. We propose a set of metrics to compare the efficiency of each technique. One of these metrics consists of the calculation of the detector pixel density, which can be also included as part of the quality control sequence in general X-ray settings. The results show a clear superiority of the DLT approach, both in accuracy and operational suitability. We paid special attention to the Zhang calibration method. Although this technique has been extensively implemented in the field of computer vision, it has rarely been tested in depth in common radiograph production scenarios. Zhang¿s approach can operate on much simpler and more affordable 2D calibration frames, which were also tested in our research. We experimentally confirm that even three or four plane-image correspondences achieve accurate focal lengths.This work was carried out with the support of Information Storage S. L., University of Valencia (Grant #CPI-15170), CSD2007-00042 Consolider Ingenio CPAN (Grant #CPAN13TR01), Spanish Ministry of Industry, Energy and Tourism (Grant #TSI-100101-2013-019), IFIC (Severo Ochoa Centre of Excellence #SEV-2014-0398), and Dr. Bellot's medical clinic.Albiol Colomer, F.; Corbi, A.; Albiol Colomer, A. (2017). Evaluation of modern camera calibration techniques for conventional diagnostic X-ray imaging settings. Radiological Physics and Technology. 10(1):68-81. https://doi.org/10.1007/s12194-016-0369-yS6881101Selby BP, Sakas G, Groch W-D, Stilla U. Patient positioning with X-ray detector self-calibration for image guided therapy. Aust Phys Eng Sci Med. 2011;34:391–400.Markelj P, Likar B. Registration of 3D and 2D medical images. PhD Thesis, University of Ljubljana; 2010.Miller T, Quintana E. Stereo X-ray system calibration for three-dimensional measurements. Springer, 2014. pp. 201–207.Rougé A, Picard C, Ponchut C, Trousset Y. Geometrical calibration of X-ray imaging chains for three-dimensional reconstruction. Comput Med Imaging Graph. 1993; 295–300.Trucco E, Verri A. Introductory techniques for 3-D computer vision. Prentice Hall Englewood Cliffs, 1998.Moura DC, Barbosa JG, Reis AM, Tavares JMRS. A flexible approach for the calibration of biplanar radiography of the spine on conventional radiological systems. Comput Model Eng Sci. 2010; 115–137.Schumann S, Thelen B, Ballestra S, Nolte L-P, Buchler P, Zheng G. X-ray image calibration and its application to clinical orthopedics. Med Eng Phys. 2014;36:968–74.Selby B, Sakas G, Walter S, Stilla U. Geometry calibration for X-ray equipment in radiation treatment devices. 2007. pp. 968–974.de Moura DC, Barbosa JMG, da Silva Tavares JMR, Reis A. Calibration of bi-planar radiography with minimal phantoms. In: Symposium on Informatics Engineering. 2008. pp. 1–10.Medioni G, Kang SB. Emerging topics in computer vision. Prentice Hall. 2004.Bushong S. Radiologic science for technologists: physics, biology, and protection. Elsevier. 2012.Rowlands JA. The physics of computed radiography. Phys Med Biol. 2002;47:123–66.Dobbins JT, Ergun DL, Rutz L, Hinshaw DA, Blume H, Clark DC. DQE(f) of four generations of computed radiography acquisition devices. Med Phys. 1995;22:1581–93.Hartley R. Self-calibration from multiple views with a rotating camera. In: European Conference on Computer Vision. 1994. pp. 471–478.Tsai R. A versatile camera calibration technique for high accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE J Robot Autom. 1985;3(4):323–44.Hartley R, Zisserman A. Multiple view geometry in computer vision. Cambridge University Press. 2004.Zhang Z. A flexible new technique for camera calibration. IEEE Trans Pattern Anal Mach Intell. 2000;22:1330–4.Remondino F, Fraser C. Digital camera calibration methods: considerations and comparisons. Symposium Image Eng Vis Metrol. 2006;36:266–72.Zollner H, Sablatnig R. Comparison of methods for geometric camera calibration using planar calibration targets. In: Digital Imaging in Media and Education. 2004. pp. 237–244

Building with Drones: Accurate 3D Facade Reconstruction using MAVs

Automatic reconstruction of 3D models from images using multi-view Structure-from-Motion methods has been one of the most fruitful outcomes of computer vision. These advances combined with the growing popularity of Micro Aerial Vehicles as an autonomous imaging platform, have made 3D vision tools ubiquitous for large number of Architecture, Engineering and Construction applications among audiences, mostly unskilled in computer vision. However, to obtain high-resolution and accurate reconstructions from a large-scale object using SfM, there are many critical constraints on the quality of image data, which often become sources of inaccuracy as the current 3D reconstruction pipelines do not facilitate the users to determine the fidelity of input data during the image acquisition. In this paper, we present and advocate a closed-loop interactive approach that performs incremental reconstruction in real-time and gives users an online feedback about the quality parameters like Ground Sampling Distance (GSD), image redundancy, etc on a surface mesh. We also propose a novel multi-scale camera network design to prevent scene drift caused by incremental map building, and release the first multi-scale image sequence dataset as a benchmark. Further, we evaluate our system on real outdoor scenes, and show that our interactive pipeline combined with a multi-scale camera network approach provides compelling accuracy in multi-view reconstruction tasks when compared against the state-of-the-art methods.Comment: 8 Pages, 2015 IEEE International Conference on Robotics and Automation (ICRA '15), Seattle, WA, US

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According to the current great interest concerning large-scale metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance are assuming a more and more important role among system requirements. This paper describes the architecture and the working principles of a novel infrared (IR) optical-based system, designed to perform low-cost and easy indoor coordinate measurements of large-size objects. The system consists of a distributed network-based layout, whose modularity allows fitting differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load. The overall system functionalities, including distributed layout configuration, network self-calibration, 3D point localization, and measurement data elaboration, are discussed. A preliminary metrological characterization of system performance, based on experimental testing, is also presente

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We propose a novel pipeline and related software tools for processing the multi-light image collections (MLICs) acquired in different application contexts to obtain shape and appearance information of captured surfaces, as well as to derive compact relightable representations of them. Our pipeline extends the popular Highlight Reflectance Transformation Imaging (H-RTI) framework, which is widely used in the Cultural Heritage domain. We support, in particular, perspective camera modeling, per-pixel interpolated light direction estimation, as well as light normalization correcting vignetting and uneven non-directional illumination. Furthermore, we propose two novel easy-to-use software tools to simplify all processing steps. The tools, in addition to support easy processing and encoding of pixel data, implement a variety of visualizations, as well as multiple reflectance-model-fitting options. Experimental tests on synthetic and real-world MLICs demonstrate the usefulness of the novel algorithmic framework and the potential benefits of the proposed tools for end-user applications.Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 665091DSURF project (PRIN 2015) funded by the Italian Ministry of University and ResearchSardinian Regional Authorities under projects VIGEC and Vis&VideoLa

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The paper addresses two problems related to 3D camera calibration using a single mono-plane calibration target with circular control marks. The first problem is how to compute accurately the locations of the features (ellipses) in images of the target. Since the structure of the control marks is known beforehand, we propose to use a shape-specific searching technique to find the optimal locations of the features. Our experiments have shown this technique generates more accurate feature locations than the state-of-the-art ellipse extraction methods. The second problem is how to refine the control mark locations with unknown manufacturing errors. We demonstrate in a case study, where the control marks are laser printed on a A4 paper, that the manufacturing errors of the control marks can be compensated to a good extent so that the remaining calibration errors are reduced significantly. 1

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