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In this paper a machine vision approach is applied to Interferometric Synthetic Aperture Radars (IFSAR) data to extract the most relevant built structures in a dense urban environment. The algorithm tries to cluster primitives (line segments) into more complex surfaces (planes) to approximate the 3D shape of these objects. Very interesting results starting from TOPSAR data recorded over S, Monica are presented.
Local disparity signals must interact in visual cortex to represent boundaries and surfaces of three-dimensional (3D) objects. We investigated how disparity signals interact in 3D contours and in 3D surfaces generated from the contours. We compared flat (single disparity) stimuli with curved (multi-disparity) stimuli. We found no consistent differences in sensitivity to contours vs. surfaces; for equivalent amounts of disparity, however, observers were more sensitive to flat stimuli than curved stimuli. Poor depth sensitivity for curved stimuli cannot be explained by the larger range of disparities present in the curved surface, nor by disparity averaging, nor by poor sensitivity to the largest disparity in the stimulus. Surprisingly, sensitivity to surfaces curved in depth was improved by removing portions of the surface and thus removing disparity information. Stimulus configuration had a profound effect on stereo thresholds that cannot be accounted for by disparity-energy models of V1 processing. We suggest that higher-level 3D contour or 3D shape mechanisms are involved.
Moore, Sterling, & Suess (2007, ApJ, 668, 1221) present evidence that (1) a CME is typically a magnetic bubble, a low-beta gplasmoid with legs h having roughly the 3D shape of a light bulb, and (2) in the outer corona the CME plasmoid is in lateral pressure equilibrium with the ambient magnetic field. They present three CMEs observed by SOHO/LASCO, each from a very different source located near the limb. One of these CMEs came from a compact ejective eruption from a small part of a sunspot active region, another came from a large quiet-region filament eruption, and the third CME, an extremely large and fast one, was produced in tandem with an X20 flare arcade that was centered on a huge delta sunspot. Each of these CMEs had more or less the classic lightbulb silhouette and attained a constant heliocentric angular width in the outer corona. This indicates that the CME plasmoid attained lateral magnetic pressure balance with the ambient radial magnetic field in the outer corona. This lateral pressure balance, together with the standard scenario for CME production by the eruption of a sheared-core magnetic arcade, yields the following simple estimate of the strength B(sub Flare) of the magnetic field in the flare arcade produced together with the CME: B(sub Flare) 1.4(theta CME/theta Flare)sup 2 G, where theta (sub CME) is the heliocentric angular width of the CME plasmoid in the outer corona and theta (sub Flare) is the heliocentric angular width of the full-grown flare arcade. Conversely, theta (sub CME) approximately equal to (R(sub Sun)sup -1(phi(sub Flare)/1.4)sup 1/2 radians, where Flare is the magnetic flux covered by the full-grown flare arcade. In addition to presenting the three CMEs of Moore, Sterling, & Suess (2007) and their agreement with this relation between CME and Flare, we present a further empirical test of this relation. For CMEs that erupt from active regions, the co-produced flare arcade seldom if ever covers the entire active region: if AR is the total magnetic flux of the active region, Flare . AR, and we predict that CME. (R(sub Sun))sup -1(theta AR/1.4)sup 1/2 radians. For a random sample of 31 CMEs that erupted from active regions within 30 of the limb, for each CME we have measured CME from LASCO/C3 and have measured AR from a SOHO/MDI magnetogram of the source active region when it was within 30 of disk center. We find that each CME obeys the above predicted inequality, none having width greater than half of the upper bound given by theta(sub AR). Thus, an active region's magnetic flux content, together with its location on the solar disk, largely determines whether the active region can possibly produce a CME that is wide enough to intercept the Earth.
NASA's twin STEREO probes, launched in 2006, have advanced the art and science of space weather forecasting more than any other spacecraft or solar observatory. By surrounding the Sun, they provide previously-impossible early warnings of threats approaching Earth as they develop on the solar far side. They have also revealed the 3D shape and inner structure of CMEs-massive solar storms that can trigger geomagnetic storms when they collide with Earth. This improves the ability of forecasters to anticipate the timing and severity of such events. Moreover, the unique capability of STEREO to track CMEs in three dimensions allows forecasters to make predictions for other planets, giving rise to the possibility of interplanetary space weather forecasting too. STEREO is one of those rare missions for which "planetary hazards" refers to more than one world. The STEREO probes also hold promise for the study of comets and potentially hazardous asteroids.
The NASA New Frontiers OSIRIS-REx spacecraft executed a flawless launch on September 8, 2016 to begin its 23-month journey to near-Earth asteroid (101955). The primary objective of the OSIRIS-REx mission is to collect and return to Earth a pristine sample of regolith from the asteroid surface. The sampling event will occur after a two-year period of remote sensing that will ensure a high probability of successful sampling of a region on the asteroid surface having high science value and within well-defined geological context. The OSIRIS-REx instrument payload includes three high-resolution cameras (OCAMS), a visible and near-infrared spectrometer (OVIRS), a thermal imaging spectrometer (OTES), an X-ray imaging spectrometer (REXIS), and a laser altimeter (OLA). As the spacecraft follows its nominal outbound-cruise trajectory, the propulsion, power, communications, and science instruments have undergone basic functional tests, with no major issues. Outbound cruise science investigations include a search for Earth Trojan asteroids as the spacecraft approaches the Sun-Earth L4 Lagrangian point in February 2017. Additional instrument checkouts and calibrations will be carried out during the Earth gravity assist maneuver in September 2017. During the Earth-moon flyby, visual and spectral images will be acquired to validate instrument command sequences planned for Bennu remote sensing. The asteroid Bennu remote sensing campaign will yield high resolution maps of the temperature and thermal inertia, distributions of major minerals and concentrations of organic matter across the asteroid surface. A high resolution 3d shape model including local surface slopes and a high-resolution gravity field will also be determined. Together, these data will be used to generate four separate maps that will be used to select the sampling site(s). The Safety map will identify hazardous and safe operational regions on the asteroid surface. The Deliverability map will quantify the accuracy with which the navigation team can deliver the spacecraft to and from specific sites on the asteroid surface. The Sampleability map quantifies the regolith properties, providing an estimation of how much material would be sampled at different points on the surface. The final Science Value map synthesizes the chemical, mineralogical, and geological, observations to identify the areas of the asteroid surface with the highest science value. Here, priority is given to organic, water-rich regions that have been minimally altered by surface processes. Asteroid surface samples will be acquired with a touch-and-go sample acquisition system (TAGSAM) that uses high purity pressurized N2 gas to mobilize regolith into a stainless steel canister. Although the mission requirement is to collect at least 60 g of material, tests of the TAGSAM routinely exceeded 300 g of simulant in micro-gravity tests. After acquiring the sample, the spacecraft will depart Bennu in 2021 to begin its return journey, with the sample return capsule landing at the Utah Test and Training Range on September 23, 2023. The OSIRIS-REx science team will carry out a series of detailed chemical, mineralogical, isotopic, and spectral studies that will be used to determine the origin and history of Bennu and to relate high spatial resolution sample studies to the global geological context from remote sensing. The outline of the sample analysis plan is described in a companion abstract.
A potential Mars Sample Return (MSR) architecture is being jointly studied by NASA and ESA. As currently envisioned, the MSR campaign consists of a series of 3 missions: sample cache, fetch and return to Earth. In this paper, we focus on the fetch part of the MSR, and more specifically the problem of autonomously detecting and localizing sample tubes deposited on the Martian surface. Towards this end, we study two machine-vision based approaches: First, a geometrydriven approach based on template matching that uses hardcoded filters and a 3D shape model of the tube; and second, a data-driven approach based on convolutional neural networks (CNNs) and learned features. Furthermore, we present a large benchmark dataset of sample-tube images, collected in representative outdoor environments and annotated with ground truth segmentation masks and locations. The dataset was acquired systematically across different terrain, illumination conditions and dust-coverage; and benchmarking was performed to study the feasibility of each approach, their relative strengths and weaknesses, and robustness in the presence of adverse environmental conditions.
We present an advanced Pole-from-Silhouette (PFS) algorithm, which is robust to illumination conditions and non-zero sun phase. PFS is an important step in the optical navigation pipeline for an autonomous small spacecraft to approach an unknown small body. The algo- rithm estimates the rotation pole and 3D shape (visual hull) of the small body using only the lit pixels within the silhouette of the small body, the body’s rotation rate, the spacecraft attitude, and the spacecraft-target relative distance, which is estimated from orbit determination. We present detailed numerical simulations and multiple sensitivity analyses to demonstrate the effectiveness of our proposed PFS algorithm in different scenarios and target bodies.
Applications of dielectric barrier discharge (DBD) based atmospheric pressure plasma jets are often limited by the relatively small area of treatment due to their 1D configuration. This system generates 2D plasma jets permitting fast treatment of larger targets. DBD evolution starts with formation of transient anode glow, and continues with development of cathode-directed streamers. The anode glow can propagate as an ionization wave along the dielectric surface through and outside of the discharge gap. Plasma propagation is not limited to 1D geometry such as tubes, and can be organized in a form of a rectangular plasma jet, or other 2D or 3D shapes. Also described are a method for generating 2D plasma jets and use of the 2D plasma jets for cancer therapy.
Experimental studies indicate that 3D crystalline metal nanoclusters (NCs) intercalated under the surface of graphite have flat-topped equilibrated shapes. In this work, we characterize the shapes of these facetted NCs sandwiched between a blanketing graphene layer and the underlying graphite substrate. Specifically, we focus on the cases of fcc Cu and hcp Fe NCs. Furthermore, the analysis involves numerical minimization of the system energy for a specified NC volume and NC height, the latter corresponding to the separation between parallel top and bottom facets. Our numerical analysis quantifies how the distance of the side facet planes from center of the nanocluster varies linearly with a natural characteristic linear dimension of the nanocluster. Calculated shapes of fcc Cu and hcp Fe NCs are consistent with the hexagonal footprints observed in scanning tunneling microscopy studies.
Abstract not provided.
Three-dimensional target identification using scattering techniques requires high accuracy solutions and very fast computations for real-time predictions in some critical applications. We first train a deep neural operator (DeepONet) to solve wave propagation problems described by the Helmholtz equation in a domain without scatterers but at different wavenumbers and with a complex absorbing boundary condition. We then design two classes of fast meta-solvers by combining DeepONet with either relaxation methods, such as Jacobi and Gauss-Seidel, or with Krylov methods, such as GMRES and BiCGStab, using the trunk basis of DeepONet as a coarse-scale preconditioner. We leverage the spectral bias of neural networks to account for the lower part of the spectrum in the error distribution while the upper part is handled inexpensively using relaxation methods or fine-scale preconditioners. The meta-solvers are then applied to solve scattering problems with different shape of scatterers, at no extra training cost. We first demonstrate that the resulting meta-solvers are shape-agnostic, fast, and robust, whereas the standard standalone solvers may even fail to converge without the DeepONet. We then apply both classes of meta-solvers to scattering from a submarine, a complex three-dimensional problem. We achieve very fast solutions, especially with the DeepONet-Krylov methods, which require orders of magnitude fewer iterations than any of the standalone solvers.
Abstract not provided.
A new system for the fusion of optical image data and polarized radar scattering cross-sections is presented. By considering the scattering data in conjunction with image data, the problem of ambiguity can be reduced. Only a small part of the surface needs to be reconstructed from the radar cross-sections; the remaining portion is constrained by the optical image.
We perform an analysis of the full shapes of Lyman-$α$ (Ly$α$) forest correlation functions measured from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). Our analysis focuses on measuring the Alcock-Paczynski (AP) effect and the cosmic growth rate times the amplitude of matter fluctuations in spheres of $8$$h^{-1}\text{Mpc}$, $fσ_8$. We validate our measurements using two different sets of mocks, a series of data splits, and a large set of analysis variations, which were first performed blinded. Our analysis constrains the ratio $D_M/D_H(z_\mathrm{eff})=4.525\pm0.071$, where $D_H=c/H(z)$ is the Hubble distance, $D_M$ is the transverse comoving distance, and the effective redshift is $z_\mathrm{eff}=2.33$. This is a factor of $2.4$ tighter than the Baryon Acoustic Oscillation (BAO) constraint from the same data. When combining with Ly$α$ BAO constraints from DESI DR2, we obtain the ratios $D_H(z_\mathrm{eff})/r_d=8.646\pm0.077$ and $D_M(z_\mathrm{eff})/r_d=38.90\pm0.38$, where $r_d$ is the sound horizon at the drag epoch. We also measure $fσ_8(z_\mathrm{eff}) = 0.37\; ^{+0.055}_{-0.065} \,(\mathrm{stat})\, \pm 0.033 \,(\mathrm{sys})$, but we do not use it for cosmological inference due to difficulties in its validation with mocks. In $Λ$CDM, our measurements are consistent with both cosmic microwave background (CMB) and galaxy clustering constraints. Using a nucleosynthesis prior but no CMB anisotropy information, we measure the Hubble constant to be $H_0 = 68.3\pm 1.6\;\,{\rm km\,s^{-1}\,Mpc^{-1}}$ within $Λ$CDM. Finally, we show that Ly$α$ forest AP measurements can help improve constraints on the dark energy equation of state, and are expected to play an important role in upcoming DESI analyses.
Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.
The three-dimensional shape and relative depth of a smoothly curving layered transparent surface may be communicated particularly effectively when the surface is artistically enhanced with sparsely distributed opaque detail. This paper describes how the set of principal directions and principal curvatures specified by local geometric operators can be understood to define a natural 'flow' over the surface of an object, and can be used to guide the placement of the lines of a stroke texture that seeks to represent 3D shape information in a perceptually intuitive way. The driving application for this work is the visualization of layered isovalue surfaces in volume data, where the particular identity of an individual surface is not generally known a priori and observers will typically wish to view a variety of different level surfaces from the same distribution, superimposed over underlying opaque structures. By advecting an evenly distributed set of tiny opaque particles, and the empty space between them, via 3D line integral convolution through the vector field defined by the principal directions and principal curvatures of the level surfaces passing through each gridpoint of a 3D volume, it is possible to generate a single scan-converted solid stroke texture that may intuitively represent the essential shape information of any level surface in the volume. To generate longer strokes over more highly curved areas, where the directional information is both most stable and most relevant, and to simultaneously downplay the visual impact of directional information in the flatter regions, one may dynamically redefine the length of the filter kernel according to the magnitude of the maximum principal curvature of the level surface at the point around which it is applied.
The effect of geometric fidelity on the aerodynamics of a swept wing with a “scallop” ice shape was studied. Three geometric fidelity versions of the ice shape were studied. The High Fidelity ice shape maintained all of the highly 3D features of the scallop shape. The 3D Smooth ice shape was smoothly lofted over the High Fidelity shape in order to eliminate all of the locally 3D feature. The third ice shape was the 3D Smooth ice shape with roughness grit attached to the surface. The two 3D Smooth versions of the ice shape exhibited a flowfield characterized by a leading edge separation bubble that rolled into spanwise running vortex. The surface pressure data showed classic leading edge separation bubbles that are observed on 2D airfoils with leading edge horn ice shapes. The High Fidelity ice shape exhibited a flowfield characterized by streamwise vortices that formed downstream of the ice shape. The streamwise vortices observed downstream of the High Fidelity ice shape appeared to reduce the size of the separation suction peak observed downstream of the 3D Smooth ice shapes. This reduced the lift for the High Fidelity ice shape, when compared to the 3D Smooth ice shapes. However, these streamwise vortices may have allowed the flow to remain attached longer and slightly increased the stall angle of attack, even though the maximum lift was lower.
Summary of GlennICE results for the Second Ice Prediction Workshop and an analysis of the effect of sweep angle on 3D ice shapes.