Ces travaux de thèse ont été menés dans le contexte du projet ANR blanc "Real Time and True Temperature measurement" (R3T), dédié à la métrologie thermique à partir de mesures dans l'infrarouge. L'estimation d'une température vraie à partir d'une mesure de température apparente par une caméra infrarouge, exploite un modèle radiométrique dans lequel apparaît des facteurs qui dépendent de la nature et de la forme de l'objet considéré. Ces travaux portent sur la construction d'un modèle géométrique de l'objet à partir de caméras infrarouges déplacées par un robot autour d'un objet.Ces caméras, par rapport à des caméras standards, ont des caractéristiques spécifiques : faible résolution, peu de texture. Afin de faciliter la mise en œuvre et de minimiser la complexité du système final, nous avons choisi une approche de stéréovision non calibrée. Nous avons donc un banc de stéréovision infrarouge embarqué sur un robot cartésien, pour acquérir plusieurs vues de l'objet d'intérêt ; les principales étapes concernent la rectification non calibrée des images acquises par le banc stéréo, puis le calibrage des caméras rectifiées et de la relation main-œil sans utilisation de mire, puis la construction de modèles 3D locaux denses et le recalage de ces modèles partiels pour construire un modèle global de l'objet. Les contributions portent sur les deux premières étapes, rectification et calibrage pour la stéréovision. Pour la rectification non calibrée, il est proposé une approche d'optimisation sous contraintes qui estime les homographies, à appliquer sur ces images pour les rectifier, sans calcul préalable de la matrice Fondamentale, tout en minimisant les déformations projectives entre images d'origine et images rectifiées. La fonction coût est calculée à partir de la distance de Sampson avec une décomposition de la matrice fondamentale. Deux types de contraintes, géométriques et algébriques, sont comparés pour minimiser les déformations projectives. L'approche proposée est comparée aux méthodes proposées par Loop et Zhang, Hartley, Mallon et al... sur des jeux de données classiques de la littérature. Il est montré que les résultats sont au moins équivalents sur des images classiques et meilleurs sur des images de faible qualité comme des images infrarouges.Pour le calibrage sans mire, l'auteur propose de calibrer les caméras ainsi que la transformation main-œil, indispensable dès lors que le banc stéréo est porté par un robot, en une seule étape ; l'une des originalités est que cette méthode permet de calibrer les caméras préalablement rectifiées et ainsi de minimiser le nombre de paramètres à estimer. De même plusieurs critères sont proposés et évalués par de nombreux résultats sur des données de synthèse et sur des données réelles. Finalement, les méthodes de stéréovision testées pour ce contexte applicatif sont rapidement décrites ; des résultats expérimentaux acquis sur des objets sont présentés ainsi que des comparaisons vis-à-vis d'une vérité terrain connue / This dissertation was lead in the context of the R3T project (Real Time and True Temperature measurement), dedicated to metrology from thermal infrared measurements. The estimation of true temperature from apparent temperature measurement by an infrared camera uses a radiometric model which depends on nature and shape of the considered object. This work focuses on the construction of a geometric model from infrared cameras moved by a robot around an object.Those cameras, in comparison with standard ones, have specific characteristics : low resolution, low texture. To minimize the complexity and easily implement the final system, we chose a stereo approach using uncalibrated cameras. So we have an infrared stereoring embeded on a Cartesian robot, to acquire multiple views of the object of interest. First, the main steps implemented concern uncalibrated images rectification and autocalibration of infrared stereoring and hand-eye transformation without use of a calibration pattern. Then, the reconstruction of locals 3D models and the merge of these models was done to reach a global model of the object. The contributions cover the first two stages, rectification and autocalibration, for the other stereo reconstruction steps, different algorithms were tested and the best was chosen for our application.For the uncalibrated images rectification, an optimization approach under constraints is proposed. The estimation of rectification homographies is done, without the Fundamental matrix determination, while minimizing the distortion between original and corrected images. The cost function is based on the Sampson's distance with breakdown of the Fundamental matrix. Two constraints, geometrical and analytical, are compared to minimize distortion. The proposed approach is compared to methods proposed by Loop and Zhang, Hartley, Mallon et al ... on data sets from state of art. It is shown that the results are at least equivalent on conventional images and better on low quality images such as infrared images.For the autocalibration, the author proposes to calibrate cameras and hand-eye transformation, essential whenever the stereoring is embedded on a robot, in one step. One of the originality is that this method allows to calibrate rectified cameras and so minimize the number of parameters to estimate. Similarly, several criteria are proposed and evaluated by numerous results on synthetic and real data.Finally, all methods of stereovision tested for this application context are briefly described, the experimental results obtained on objects are presented and compared to ground truth

Indiana University-Purdue University Indianapolis (IUPUI) / The geometric and electrochemical characteristics of different lithium ion batteries (LIBs) are investigated in this study. The core work is to study the impact of the calendering process on NMC cathode electrodes performance. X-ray CT image processing by Python, MATLAB, ImageJ and Avizo is utilized in this study. NMC electrodes with different calendering conditions were fabricated to calculate electrochemical properties of the cells. Charge/discharge of the electrodes under 0.1C, 0.2C, 0.4C, 1C, 2C, 4C and 0.1C (retention test) rates were cycled for three times respectively between 4.2 V and 3.0 V. Electrochemical impedance spectroscopy testing was used to further explain the effects of NMC density on rate capability. Geometric properties of NMC electrodes with different calendering conditions were calculated from the computed tomography data of the electrodes. A synchrotron transmission X-ray microscopy tomography system at the Advanced Photon Source of the Argonne National Laboratory was employed to obtain the tomography data. X-ray CT image processing before the data analysis was introduced. Python based Tomopy and ASTRA toolbox were used to filter the original HDF5 data and reconstruction. ImageJ was used to help remove noise, adjust contrast and cropping. Iso2mesh and image processing tool box were used in MATLAB to generate meshed 3D structure of CT data. Geometric properties of NMC electrodes including porosity, pore size distribution, particle size distribution, specific surface area and tortuosity were calculated from the computed tomography data of the electrodes. The geometric and electrochemical analysis show that calendering can increase the electrochemically active area, which lead to improving of the rate capability. However, more calendering will result in crushing of NMC particles, which can reduce the electrode capacity at relatively high C rates. This study shows that the optimum electrochemical performance of NMC electrode at 94:3:3 weight ratio of NMC:binder:carbon black can be achieved by calendering to 3.0 g/cm3 NMC density. LTAP solid electrolyte and NMC cathode material mix electrode-electrolyte X-ray CT data was studied in last chapter. By using 8 kev X-ray energy, we could distinguish NMC active material, LTAP solid electrolyte and the others three phase. On the basis of NMC electrode image processing method, dilation and multiply threshold method is applied to get three-phase 3D geometry. A comparing of connection area between NMC and LTAP of 700psi and 1300psi electrode was analyzed. Geometric properties like tortuosity, di_usion length and e_ective di_usivity were generated from the CT data.

This diploma thesis is devoted to the use of 3D reconstruction using EBSD method for microstructural analysis of silicon nitride ceramic material predetermined for the rolling-mill used in the wire production. Application of this method can be used for the grain structure reconstruction and basic microstructural parameters can be than extracted. The development of a suitable method for 3D reconstruction of the structure of the materials the main aim of this work. There are described the different steps begun by sample preparation from the investigated material trough the optimisation of analysis parameters up to the visualization of the grain structure. New type of sample geometry has been designed which leads to the better and faster observation of the microstructure of ceramic materials. This thesis also describes optimal reconstruction parameters such as the geometry of the assembly used in the microscope without mechanical movement of the sample or the influence of conductive coating prepared via in-situ sputtering of suitable metal, or adjustment of the electron and ion beams. Further are described two options of software which can be used for the final generation of 3D structure information and are assessed their advantages and disadvantages. The effect of the filter setting and other parameters and their influence on the resulting structural parameters are also evaluated.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19700号 / 工博第4155号 / 新制||工||1641(附属図書館) / 32736 / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 井手 亜里, 教授 松野 文俊, 教授 蓮尾 昌裕 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

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We give a concise explication of the theory of level set methods for modeling motion of an interface as well as the numerical implementation of these methods. We then introduce the geometry of a camera and the mathematical models for 3D reconstruction with a few examples both simulated and from a real camera. We finally describe the model for 3D surface reconstruction from n-camera views using level set methods.

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Multi-camera systems are becoming ubiquitous and have found application in a variety of domains including surveillance, immersive visualization, sports entertainment and movie special effects amongst others. From a computer vision perspective, the challenging task is how to most efficiently fuse information from multiple views in the absence of detailed calibration information and a minimum of human intervention. This thesis presents a new approach to fuse foreground likelihood information from multiple views onto a reference view without explicit processing in 3D space, thereby circumventing the need for complete calibration. Our approach uses a homographic occupancy constraint (HOC), which states that if a foreground pixel has a piercing point that is occupied by foreground object, then the pixel warps to foreground regions in every view under homographies induced by the reference plane, in effect using cameras as occupancy detectors. Using the HOC we are able to resolve occlusions and robustly determine ground plane localizations of the people in the scene. To find tracks we obtain ground localizations over a window of frames and stack them creating a space time volume. Regions belonging to the same person form contiguous spatio-temporal tracks that are clustered using a graph cuts segmentation approach. Second, we demonstrate that the HOC is equivalent to performing visual hull intersection in the image-plane, resulting in a cross-sectional slice of the object. The process is extended to multiple planes parallel to the reference plane in the framework of plane to plane homologies. Slices from multiple planes are accumulated and the 3D structure of the object is segmented out. Unlike other visual hull based approaches that use 3D constructs like visual cones, voxels or polygonal meshes requiring calibrated views, ours is purely-image based and uses only 2D constructs i.e. planar homographies between views. This feature also renders it conducive to graphics hardware acceleration. The current GPU implementation of our approach is capable of fusing 60 views (480x720 pixels) at the rate of 50 slices/second. We then present an extension of this approach to reconstructing non-rigid articulated objects from monocular video sequences. The basic premise is that due to motion of the object, scene occupancies are blurred out with non-occupancies in a manner analogous to motion blurred imagery. Using our HOC and a novel construct: the temporal occupancy point (TOP), we are able to fuse multiple views of non-rigid objects obtained from a monocular video sequence. The result is a set of blurred scene occupancy images in the corresponding views, where the values at each pixel correspond to the fraction of total time duration that the pixel observed an occupied scene location. We then use a motion de-blurring approach to de-blur the occupancy images and obtain the 3D structure of the non-rigid object. In the final part of this thesis, we present an object class detection method employing 3D models of rigid objects constructed using the above 3D reconstruction approach. Instead of using a complicated mechanism for relating multiple 2D training views, our approach establishes spatial connections between these views by mapping them directly to the surface of a 3D model. To generalize the model for object class detection, features from supplemental views (obtained from Google Image search) are also considered. Given a 2D test image, correspondences between the 3D feature model and the testing view are identified by matching the detected features. Based on the 3D locations of the corresponding features, several hypotheses of viewing planes can be made. The one with the highest confidence is then used to detect the object using feature location matching. Performance of the proposed method has been evaluated by using the PASCAL VOC challenge dataset and promising results are demonstrated.

The thesis deals with incorporating the shape-from-shading technique into the multi-view stereo (MVS) reconstruction framework using the Oren-Nayar reflectance model for rough natural materials. Two methods for enhancing the MVS algorithm with new photo-consistency measure are proposed. Experiments with the laboratory images as well as with images of Mars's surface were conducted, proving that the proposed plane-sweeping method using shading information suitable for combining with MVS can nd the correct position of surface in 3D scene. The experiments also showed, that the Oren-Nayar reflectance model is very accurate for some real-world materials and it can be succesfuly used in the plane-sweeping method to accomplish better results than the Lambert's reflectance model. With precisely estimated material parameters and the light source and camera directions, it is possible to achieve the accuracy of few centimeters in estimating the position of real surface in the scene. / <p>Validerat; 20110825 (anonymous)</p>