Virtual Rephotography: Novel View Prediction Error for 3D Reconstruction

The ultimate goal of many image-based modeling systems is to render photo-realistic novel views of a scene without visible artifacts. Existing evaluation metrics and benchmarks focus mainly on the geometric accuracy of the reconstructed model, which is, however, a poor predictor of visual accuracy. Furthermore, using only geometric accuracy by itself does not allow evaluating systems that either lack a geometric scene representation or utilize coarse proxy geometry. Examples include light field or image-based rendering systems. We propose a unified evaluation approach based on novel view prediction error that is able to analyze the visual quality of any method that can render novel views from input images. One of the key advantages of this approach is that it does not require ground truth geometry. This dramatically simplifies the creation of test datasets and benchmarks. It also allows us to evaluate the quality of an unknown scene during the acquisition and reconstruction process, which is useful for acquisition planning. We evaluate our approach on a range of methods including standard geometry-plus-texture pipelines as well as image-based rendering techniques, compare it to existing geometry-based benchmarks, and demonstrate its utility for a range of use cases.Comment: 10 pages, 12 figures, paper was submitted to ACM Transactions on Graphics for revie

Investigating GNSS multipath effects induced by co-located Radar Corner Reflectors

Abstract Radar Corner Reflectors (CR) are increasingly used as reference targets for land surface deformation measurements with the Interferometric Synthetic Aperture Radar (InSAR) technique. When co-located with ground-based Global Navigation Satellite Systems (GNSS) infrastructure, InSAR observations at CR can be used to integrate relative measurements of surface deformation into absolute reference frames defined by GNSS. However, CR are also a potential source of GNSS multipath effects and may therefore have a detrimental effect on the GNSS observations. In this study, we compare daily GNSS coordinate time series and 30-second signal-to-noise ratio (SNR) observations for periods before and after CR deployment at a GNSS site. We find that neither the site coordinates nor the SNR values are significantly affected by the CR deployment, with average changes being within 0.1 mm for site coordinates and within 1 % for SNR values. Furthermore, we generate empirical site models by spatially stacking GNSS observation residuals to visualise and compare the spatial pattern in the surroundings of GNSS sites. The resulting stacking maps indicate oscillating patterns at elevation angles above 60 degrees which can be attributed to the CR deployed at the analysed sites. The effect depends on the GNSS antenna used at a site with the magnitude of multipath patterns being around three times smaller for a high-quality choke ring antenna compared to a ground plane antenna without choke rings. In general, the CR-induced multipath is small compared to multipath effects at other GNSS sites located in a different environment (e. g. mounted on a building)

Scene Reconstruction from Multi-Scale Input Data

Geometry acquisition of real-world objects by means of 3D scanning or stereo reconstruction constitutes a very important and challenging problem in computer vision. 3D scanners and stereo algorithms usually provide geometry from one viewpoint only, and several of the these scans need to be merged into one consistent representation. Scanner data generally has lower noise levels than stereo methods and the scanning scenario is more controlled. In image-based stereo approaches, the aim is to reconstruct the 3D surface of an object solely from multiple photos of the object. In many cases, the stereo geometry is contaminated with noise and outliers, and exhibits large variations in scale. Approaches that fuse such data into one consistent surface must be resilient to such imperfections. In this thesis, we take a closer look at geometry reconstruction using both scanner data and the more challenging image-based scene reconstruction approaches. In particular, this work focuses on the uncontrolled setting where the input images are not constrained, may be taken with different camera models, under different lighting and weather conditions, and from vastly different points of view. A typical dataset contains many views that observe the scene from an overview perspective, and relatively few views capture small details of the geometry. What results from these datasets are surface samples of the scene with vastly different resolution. As we will show in this thesis, the multi-resolution, or, "multi-scale" nature of the input is a relevant aspect for surface reconstruction, which has rarely been considered in literature yet. Integrating scale as additional information in the reconstruction process can make a substantial difference in surface quality. We develop and study two different approaches for surface reconstruction that are able to cope with the challenges resulting from uncontrolled images. The first approach implements surface reconstruction by fusion of depth maps using a multi-scale hierarchical signed distance function. The hierarchical representation allows fusion of multi-resolution depth maps without mixing geometric information at incompatible scales, which preserves detail in high-resolution regions. An incomplete octree is constructed by incrementally adding triangulated depth maps to the hierarchy, which leads to scattered samples of the multi-resolution signed distance function. A continuous representation of the scattered data is defined by constructing a tetrahedral complex, and a final, highly-adaptive surface is extracted by applying the Marching Tetrahedra algorithm. A second, point-based approach is based on a more abstract, multi-scale implicit function defined as a sum of basis functions. Each input sample contributes a single basis function which is parameterized solely by the sample's attributes, effectively yielding a parameter-free method. Because the scale of each sample controls the size of the basis function, the method automatically adapts to data redundancy for noise reduction and is highly resilient to the quality-degrading effects of low-resolution samples, thus favoring high-resolution surfaces. Furthermore, we present a robust, image-based reconstruction system for surface modeling: MVE, the Multi-View Environment. The implementation provides all steps involved in the pipeline: Calibration and registration of the input images, dense geometry reconstruction by means of stereo, a surface reconstruction step and post-processing, such as remeshing and texturing. In contrast to other software solutions for image-based reconstruction, MVE handles large, uncontrolled, multi-scale datasets as well as input from more controlled capture scenarios. The reason lies in the particular choice of the multi-view stereo and surface reconstruction algorithms. The resulting surfaces are represented using a triangular mesh, which is a piecewise linear approximation to the real surface. The individual triangles are often so small that they barely contribute any geometric information and can be ill-shaped, which can cause numerical problems. A surface remeshing approach is introduced which changes the surface discretization such that more favorable triangles are created. It distributes the vertices of the mesh according to a density function, which is derived from the curvature of the geometry. Such a mesh is better suited for further processing and has reduced storage requirements. We thoroughly compare the developed methods against the state-of-the art and also perform a qualitative evaluation of the two surface reconstruction methods on a wide range of datasets with different properties. The usefulness of the remeshing approach is demonstrated on both scanner and multi-view stereo data

Simulative Comparison of Radiation Model Parameterizations for Direct Current Arcs in a Busbar Setup

The influence of different methods for calculating mean absorption coefficients on the mean arc voltage and velocity of an arc moving in air along parallel busbars is investigated in a numerical arc simulation. The radiation model used is the discrete ordinate method. Planck, hybrid and Rosseland mean calculations for a three- and six-band selection are discussed. Compared with the experimental results from a published paper, the Planck mean for six bands shows the most promising results

Near-uniform internal rotation of the main-sequence γ Doradus pulsator KIC 7661054

We used Kepler photometry to determine the internal rotation rate of KIC 7661054, a chemically normal γ Dor star on the main sequence at spectral type F2.5 V. The core rotation period of 27.25 ± 0.06 d is obtained from the rotational splittings of a series of dipole g modes. The surface rotation period is calculated from a spectroscopic projected rotation velocity and a stellar radius computed from models. Literature data, obtained without inclusion of macroturbulence as a line-broadening mechanism, imply that the surface rotates much more quickly than the core, while our detailed analysis suggests that the surface may rotate slightly more quickly than the core and that the rotation profile is uniform within the 1-σ uncertainties. We discuss the pitfalls associated with the determination of surface rotation rates of slow rotators from spectroscopy in the absence of asteroseismic constraints. A broad signal is observed at low frequency, which we show cannot be attributed to rotation, contrary to previous suggestions concerning the origin of such signals

The SPLASH Survey: A Spectroscopic Portrait of Andromeda's Giant Southern Stream

The giant southern stream (GSS) is the most prominent tidal debris feature in M31's stellar halo. The GSS is composed of a relatively metal-rich, high surface-brightness "core" and a lower metallicity, lower surface brightness "envelope." We present Keck/DEIMOS spectroscopy of red giant stars in six fields in the vicinity of M31's GSS and one field on Stream C, an arc-like feature on M31's SE minor axis at R=60 kpc. Several GSS-related findings and measurements are presented here. We present the innermost kinematical detection of the GSS core to date (R=17 kpc). This field also contains the continuation of a second kinematically cold component originally seen in a GSS core field at R=21 kpc. The velocity gradients of the GSS and the second component in the combined data set are parallel over a radial range of 7 kpc, suggesting a possible bifurcation in the line-of-sight velocities of GSS stars. We also present the first kinematical detection of substructure in the GSS envelope. Using kinematically identified samples, we show that the envelope debris has a ~0.7 dex lower mean photometric metallicity and possibly higher intrinsic velocity dispersion than the GSS core. The GSS is also identified in the field of the M31 dSph satellite And I; the GSS in this field has a metallicity distribution identical to that of the GSS core. We confirm the presence of two kinematically cold components in Stream C, and measure intrinsic velocity dispersions of ~10 and ~4 km/s. This compilation of the kinematical (mean velocity, intrinsic velocity dispersion) and chemical properties of stars in the GSS core and envelope, coupled with published surface brightness measurements and wide-area star-count maps, will improve constraints on the orbit and internal structure of the dwarf satellite progenitor.Comment: Accepted for publication in Ap