Multiview photometric stereo

This paper addresses the problem of obtaining complete, detailed reconstructions of textureless shiny objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under changing illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint but produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object's visual hull. This is then used to recover the illumination and initialize a multiview photometric stereo scheme to obtain a closed surface reconstruction. There are two main contributions in this paper: First, we describe a robust technique to estimate light directions and intensities and, second, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and, hence, allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with complete reconstructions of challenging real objects. Finally, we show experimentally how, even in the case of highly textured objects, this technique can greatly improve on correspondence-based multiview stereo results.

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

Sensitivity analysis in optimized parametric curve fitting

Purpose – Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications -- In the literature, several approaches have been proposed to solve this problem -- However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k), and point sample size (r) on the optimized curve reconstruction measured by a penalty function (f) -- The paper aims to discuss these issues -- Design/methodology/approach - A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed -- Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored -- Findings - It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m -- Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks -- The authors were able to detect the presence of such spurious features with spectral analysis -- Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample -- Research limitations/implications - The authors have addressed important voids of previous works in this field -- The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how -- Also, the authors performed a characterization of the curve fitting problem from the optimization perspective -- And finally, the authors devised a method to detect spurious features in the fitting curve -- Practical implications – This paper provides a methodology to select the important tuning parameters in a formal manner -- Originality/value - Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.)

Reconstruction of core and surface nanoparticles: The example of Pt(55) and Au(55)

Cuboctahedron (CUB) and icosahedron (ICO) model structures are widely used in the study of transition-metal (TM) nanoparticles (NPs), however, it might not provide a reliable description for small TM NPs such as the Pt(55) and Au(55) systems in gas phase. In this work, we combined density-functional theory calculations with atomic configurations generated by the basin hopping Monte Carlo algorithm within the empirical Sutton-Chen embedded atom potential. We identified alternative lower energy configurations compared with the ICO and CUB model structures, e. g., our lowest energy structures are 5.22 eV (Pt(55)) and 2.01 eV (Au(55)) lower than ICO. The energy gain is obtained by the Pt and Au diffusion from the ICO core region to the NP surface, which is driven by surface compression (only 12 atoms) on the ICO core region. Therefore, in the lowest energy configurations, the core size reduces from 13 atoms (ICO, CUB) to about 9 atoms while the NP surface increases from 42 atoms (ICO, CUB) to about 46 atoms. The present mechanism can provide an improved atom-level understanding of small TM NPs reconstructions.

Reconstruction of the surface of the Sun from stereoscopic images

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Evaluating the efficacy of planktonic foraminifer calcite and 18O data for sea surface temperature reconstruction for the Late Miocene

This study examines the efficacy of published δ18O data from the calcite of Late Miocene surface dwelling planktonic foraminifer shells, for sea surface temperature estimates for the pre-Quaternary. The data are from 33 Late Miocene (Messinian) marine sites from a modern latitudinal gradient of 64°N to 48°S. They give estimates of SSTs in the tropics/subtropics (to 30°N and S) that are mostly cooler than present. Possible causes of this temperature discrepancy are ecological factors (e.g. calcification of shells at levels below the ocean mixed layer), taphonomic effects (e.g. diagenesis or dissolution), inaccurate estimation of Late Miocene seawater oxygen isotope composition, or a real Late Miocene cool climate. The scale of apparent cooling in the tropics suggests that the SST signal of the foraminifer calcite has been reset, at least in part, by early diagenetic calcite with higher δ18O, formed in the foraminifer shells in cool sea bottom pore waters, probably coupled with the effects of calcite formed below the mixed layer during the life of the foraminifera. This hypothesis is supported by the markedly cooler SST estimates from low latitudes—in some cases more than 9 °C cooler than present—where the gradients of temperature and the δ18O composition of seawater between sea surface and sea bottom are most marked, and where ocean surface stratification is high. At higher latitudes, particularly N and S of 30°, the temperature signal is still cooler, though maximum temperature estimates overlap with modern SSTs N and S of 40°. Comparison of SST estimates for the Late Miocene from alkenone unsaturation analysis from the eastern tropical Atlantic at Ocean Drilling Program (ODP) Site 958—which suggest a warmer sea surface by 2–4 °C, with estimates from oxygen isotopes at Deep Sea Drilling Project (DSDP) Site 366 and ODP Site 959, indicating cooler than present SSTs, also suggest a significant impact on the δ18O signal. Nevertheless, much of the original SST variation is clearly preserved in the primary calcite formed in the mixed layer, and records secular and temporal oceanographic changes at the sea surface, such as movement of the Antarctic Polar Front in the Southern Ocean. Cooler SSTs in the tropics and sub-tropics are also consistent with the Late Miocene latitude reduction in the coral reef belt and with interrupted reef growth on the Queensland Plateau of eastern Australia, though it is not possible to quantify absolute SSTs with the existing oxygen isotope data. Reconstruction of an accurate global SST dataset for Neogene time-slices from the existing published DSDP/ODP isotope data, for use in general circulation models, may require a detailed re-assessment of taphonomy at many sites.

Evaluating the efficacy of planktonic foraminifer calcite and 18O data for sea surface temperature reconstruction for the Late Miocene

This study examines the efficacy of published δ18O data from the calcite of Late Miocene surface dwelling planktonic foraminifer shells, for sea surface temperature estimates for the pre-Quaternary. The data are from 33 Late Miocene (Messinian) marine sites from a modern latitudinal gradient of 64°N to 48°S. They give estimates of SSTs in the tropics/subtropics (to 30°N and S) that are mostly cooler than present. Possible causes of this temperature discrepancy are ecological factors (e.g. calcification of shells at levels below the ocean mixed layer), taphonomic effects (e.g. diagenesis or dissolution), inaccurate estimation of Late Miocene seawater oxygen isotope composition, or a real Late Miocene cool climate. The scale of apparent cooling in the tropics suggests that the SST signal of the foraminifer calcite has been reset, at least in part, by early diagenetic calcite with higher δ18O, formed in the foraminifer shells in cool sea bottom pore waters, probably coupled with the effects of calcite formed below the mixed layer during the life of the foraminifera. This hypothesis is supported by the markedly cooler SST estimates from low latitudes—in some cases more than 9 °C cooler than present—where the gradients of temperature and the δ18O composition of seawater between sea surface and sea bottom are most marked, and where ocean surface stratification is high. At higher latitudes, particularly N and S of 30°, the temperature signal is still cooler, though maximum temperature estimates overlap with modern SSTs N and S of 40°. Comparison of SST estimates for the Late Miocene from alkenone unsaturation analysis from the eastern tropical Atlantic at Ocean Drilling Program (ODP) Site 958—which suggest a warmer sea surface by 2–4 °C, with estimates from oxygen isotopes at Deep Sea Drilling Project (DSDP) Site 366 and ODP Site 959, indicating cooler than present SSTs, also suggest a significant impact on the δ18O signal. Nevertheless, much of the original SST variation is clearly preserved in the primary calcite formed in the mixed layer, and records secular and temporal oceanographic changes at the sea surface, such as movement of the Antarctic Polar Front in the Southern Ocean. Cooler SSTs in the tropics and sub-tropics are also consistent with the Late Miocene latitude reduction in the coral reef belt and with interrupted reef growth on the Queensland Plateau of eastern Australia, though it is not possible to quantify absolute SSTs with the existing oxygen isotope data. Reconstruction of an accurate global SST dataset for Neogene time-slices from the existing published DSDP/ODP isotope data, for use in general circulation models, may require a detailed re-assessment of taphonomy at many sites.

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

Application of 3D documentation and geometric reconstruction methods in traffic accident analysis: with high resolution surface scanning, radiological MSCT/MRI scanning and real data based animation

The examination of traffic accidents is daily routine in forensic medicine. An important question in the analysis of the victims of traffic accidents, for example in collisions between motor vehicles and pedestrians or cyclists, is the situation of the impact. Apart from forensic medical examinations (external examination and autopsy), three-dimensional technologies and methods are gaining importance in forensic investigations. Besides the post-mortem multi-slice computed tomography (MSCT) and magnetic resonance imaging (MRI) for the documentation and analysis of internal findings, highly precise 3D surface scanning is employed for the documentation of the external body findings and of injury-inflicting instruments. The correlation of injuries of the body to the injury-inflicting object and the accident mechanism are of great importance. The applied methods include documentation of the external and internal body and the involved vehicles and inflicting tools as well as the analysis of the acquired data. The body surface and the accident vehicles with their damages were digitized by 3D surface scanning. For the internal findings of the body, post-mortem MSCT and MRI were used. The analysis included the processing of the obtained data to 3D models, determination of the driving direction of the vehicle, correlation of injuries to the vehicle damages, geometric determination of the impact situation and evaluation of further findings of the accident. In the following article, the benefits of the 3D documentation and computer-assisted, drawn-to-scale 3D comparisons of the relevant injuries with the damages to the vehicle in the analysis of the course of accidents, especially with regard to the impact situation, are shown on two examined cases.