Creating virtual models from uncalibrated camera views

The reconstruction of photorealistic 3D models from camera views is becoming an ubiquitous element in many applications that simulate physical interaction with the real world. In this paper, we present a low-cost, interactive pipeline aimed at non-expert users, that achieves 3D reconstruction from multiple views acquired with a standard digital camera. 3D models are amenable to access through diverse representation modalities that typically imply trade-offs between level of detail, interaction, and computational costs. Our approach allows users to selectively control the complexity of different surface regions, while requiring only simple 2D image editing operations. An initial reconstruction at coarse resolution is followed by an iterative refining of the surface areas corresponding to the selected regions

A self-consistent empirical model atmosphere, abundance and stratification analysis of the benchmark roAp star alpha Circini

Chemically peculiar (CP) stars are unique natural laboratories for investigation of the microscopic diffusion processes of chemical elements. The element segregation under the influence of gravity and radiation pressure leads to the appearance of strong abundance gradients in the atmospheres of CP stars. Consequently, the atmospheric temperature-pressure structure of these objects could deviate significantly from the atmospheres of normal stars with homogeneous abundances. In this study we performed a self-consistent, empirical model atmosphere study of the brightest rapidly oscillating Ap star alpha Cir. We account for chemical stratification in the model atmosphere calculations and assess the importance of non-uniformed vertical element distribution on the model structure, energy distribution and hydrogen line profiles. Based on an iterative procedure of the chemical abundance analysis of 52 ions of 35 elements, stratification modeling of 4 elements (Si, Ca, Cr and Fe) and subsequent re-calculations of the atmospheric structure, we derived a new model atmosphere of alpha Cir, which is consistent with the inferred atmospheric chemistry of the star. We find Teff=7500 K, logg=4.1, and demonstrate that chemical stratification has a noticeable impact on the model structure and modifies the formation of the hydrogen Balmer lines. Our spectroscopically determined Teff of alpha Cir agrees with the fundamental effective temperature of this star. This shows that temperatures inferred in detailed spectroscopic analyses of cool magnetic CP stars are not affected by a large systematic bias.Comment: 14 pages, 11 figures; accepted for publication in Astronomy & Astrophysic

Mapping the Galaxy Color-Redshift Relation: Optimal Photometric Redshift Calibration Strategies for Cosmology Surveys

Calibrating the photometric redshifts of >10^9 galaxies for upcoming weak lensing cosmology experiments is a major challenge for the astrophysics community. The path to obtaining the required spectroscopic redshifts for training and calibration is daunting, given the anticipated depths of the surveys and the difficulty in obtaining secure redshifts for some faint galaxy populations. Here we present an analysis of the problem based on the self-organizing map, a method of mapping the distribution of data in a high-dimensional space and projecting it onto a lower-dimensional representation. We apply this method to existing photometric data from the COSMOS survey selected to approximate the anticipated Euclid weak lensing sample, enabling us to robustly map the empirical distribution of galaxies in the multidimensional color space defined by the expected Euclid filters. Mapping this multicolor distribution lets us determine where - in galaxy color space - redshifts from current spectroscopic surveys exist and where they are systematically missing. Crucially, the method lets us determine whether a spectroscopic training sample is representative of the full photometric space occupied by the galaxies in a survey. We explore optimal sampling techniques and estimate the additional spectroscopy needed to map out the color-redshift relation, finding that sampling the galaxy distribution in color space in a systematic way can efficiently meet the calibration requirements. While the analysis presented here focuses on the Euclid survey, similar analysis can be applied to other surveys facing the same calibration challenge, such as DES, LSST, and WFIRST.Comment: ApJ accepted, 17 pages, 10 figure

Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction of a rigid scene, we address the problem of the autocalibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. We propose an algorithm that only requires 5 cameras (the theoretical minimum), thus halving the number of cameras required by previous algorithms based on the same constraint. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient way. This parameterization is then used to solve autocalibration from five or more cameras, reducing the three-dimensional search space to a two-dimensional one. We provide experiments with real images showing the good performance of the technique.Comment: 19 pages, 14 figures, 7 tables, J. Math. Imaging Vi

Geometrical Product Specification and Verification as toolbox to meet up-to-date technical requirements

The ISO standards for the Geometrical Product Specification and Verification (GPS) define an internationally uniform description language, that allows expressing unambiguously and completely all requirements for the geometry of a product with the corresponding requirements for the inspection process in technical drawings, taking into account current possibilities of measurement and testing technology. The practice shows that the university curricula of the mechanical engineering faculties often include only limited classes on the GPS, mostly as part of curriculum of subjects like Metrology or Fundamentals of Machine Design. This does not allow students to gain enough knowledge on the subject. Currently there is no coherent EU-wide provision for vocational training (VET) in this area. Consortium, members of which are the authors of this paper, is preparing a proposal of an EU project aiming to develop appropriate course

QUARCH: A New Quasi-Affine Reconstruction Stratum From Vague Relative Camera Orientation Knowledge

International audienceWe present a new quasi-affine reconstruction of a scene and its application to camera self-calibration. We refer to this reconstruction as QUARCH (QUasi-Affine Reconstruction with respect to Camera centers and the Hodographs of horopters). A QUARCH can be obtained by solving a semidefinite programming problem when, (i) the images have been captured by a moving camera with constant intrinsic parameters, and (ii) a vague knowledge of the relative orientation (under or over 120°) between camera pairs is available. The resulting reconstruction comes close enough to an affine one allowing thus an easy upgrade of the QUARCH to its affine and metric counterparts. We also present a constrained Levenberg-Marquardt method for nonlinear optimization subject to Linear Matrix Inequality (LMI) constraints so as to ensure that the QUARCH LMIs are satisfied during optimization. Experiments with synthetic and real data show the benefits of QUARCH in reliably obtaining a metric reconstruction

QUARCH: A New Quasi-Affine Reconstruction Stratum From Vague Relative Camera Orientation Knowledge

International audienceWe present a new quasi-affine reconstruction of a scene and its application to camera self-calibration. We refer to this reconstruction as QUARCH (QUasi-Affine Reconstruction with respect to Camera centers and the Hodographs of horopters). A QUARCH can be obtained by solving a semidefinite programming problem when, (i) the images have been captured by a moving camera with constant intrinsic parameters, and (ii) a vague knowledge of the relative orientation (under or over 120°) between camera pairs is available. The resulting reconstruction comes close enough to an affine one allowing thus an easy upgrade of the QUARCH to its affine and metric counterparts. We also present a constrained Levenberg-Marquardt method for nonlinear optimization subject to Linear Matrix Inequality (LMI) constraints so as to ensure that the QUARCH LMIs are satisfied during optimization. Experiments with synthetic and real data show the benefits of QUARCH in reliably obtaining a metric reconstruction