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In this article, the significant radar cross section (RCS) reduction of curved surfaces in the low microwave frequency band is reported. The design method of partition layout loading of frequency selective surface (FSS) absorbers to control the surface current is put forward. Comparison of the scattering field intensities of different zones on the curved surface clearly shows that surface current should be suppressed in a large zone to effectively reduce the RCS of the curved surface at these frequencies. FSS absorbers under normal and 45° angle of incidence are designed and placed on the different zones of the curved surface to realize the partition layout loading, and remarkable RCS reduction has been obtained. Specifically, more than 15-dB RCS reduction is achieved in 1.05–1.45 GHz, and absorption above 90% is obtained from 0.95 to 1.5 GHz for TE polarization. The great agreement between the simulated and measured results validates the proposed design method. [ABSTRACT FROM AUTHOR]

A novel sensor tag based on spit ring resonator (SRR) for detecting cracks on curved metal surfaces is presented in this paper. This tag is flexible and can be easily covered on the surface of curved metal structure. The SRR shape is etched on the tag, which is excited by the waveguide to make it resonate. Accurate crack detection can be achieved based on the resonance frequency shift caused by the crack. Due to the strong field enhancement effect during SRR resonance, the tag is highly sensitive in detecting metal cracks. When the radius of the curved film-coated metal is 40mm, there will be a resonant frequency shift greater than 260MHz when detecting sub-millimeter cracks of different sizes. And a resonance frequency shift of at least 100MHz is still exhibit when a 10 $\mu {\mathrm{ m}}$ microcrack is detected. This tag is expected to provide a new idea for high-precision surface crack detection of curved metals. [ABSTRACT FROM AUTHOR]

Efficient and accurate radio propagation modeling is essential for optimization of both radio sensing and communication systems. However, highly accurate full-wave methods remain inefficient at high frequencies, as unit of computation has to be made much smaller than the wavelength. On the other hand, ray-based approaches offer the desired speed, but the surface element (typically, a triangle) must be made much larger than the wavelength, thus making it difficult to represent complex curved surfaces of common objects, such as cars or unmanned aerial vehicles. As a result, for super high frequency (SHF)/extremely high frequency (EHF) bands, it is challenging to select a method that is both fast and capable of capturing curved surfaces correctly. To address this issue, we present a method that offers a reasonable tradeoff between speed and accuracy for radio propagation modeling in the bands of interest. Specifically, we combine efficient voxel scene representation targeting a cone tracing algorithm with a statistical scattering model. To confirm the validity of our approach, we report the dependence of reflected power on the distance for basic primitives, such as cone and sphere, for which closed-form radar cross-section solutions are known. We demonstrate that the proposed approach is superior compared to the conventional ray-tracing solutions, while posing no restrictions for efficient voxel cone tracing implementations. [ABSTRACT FROM AUTHOR]

Airborne light detection and ranging (LiDAR) data are widely applied in building reconstruction, with studies reporting success in typical buildings. However, the reconstruction of curved buildings remains an open research problem. To this end, we propose a new framework for curved building reconstruction via assembling and deforming geometric primitives. The input LiDAR point clouds are first converted into contours where individual buildings are identified. After recognizing geometric units (primitives) from building contours, we get initial models by matching the basic geometric primitives to these primitives. To polish assembly models, we employ a warping field for model refinements. Specifically, an embedded deformation (ED) graph is constructed via downsampling the initial model. Then, the point to model displacements is minimized by adjusting node parameters in the ED graph based on our objective function. The presented framework is validated on several highly curved buildings collected by various LiDAR in different cities. The experimental results, as well as accuracy comparison, demonstrate the advantage and effectiveness of our method. The new insight attributes to an efficient reconstruction manner. Moreover, we prove that the primitive-based framework significantly reduces the data storage to 10%–20% of classical mesh models. [ABSTRACT FROM AUTHOR]

This paper presents an analytical model to study the sensing performance of the flexible capacitive tactile sensor array when mounted on a curved surface. To predict the deformation of the sensor unit, a cylindrical coordinate is constructed for the upper Polyethylene Terephthalate (PET) and truncated pyramids dielectric layer. The displacement functions model is developed and solved by using the Ritz method. Then, this model is utilized to investigate the capacitance change of the sensor unit and the model-calculated results are compared with the experiment data. Both model calculated and experiment measured results indicate that the capacitances of the sensor array are increased by about 30% when the sensor is mounted on the curved surface with a radius of curvature of 10 mm. Due to the bending effects of the curved surface, the sensitivities of the sensor array are decreased based on the model calculation and are confirmed by experimental validation. Thus, results demonstrate that the developed analytical model can accurately predict the sensing performance of the tactile sensor array on the curved surface and could be utilized for the real applications. [2016-0235] [ABSTRACT FROM AUTHOR]

Recent advances in very high resolution tomographic synthetic aperture radar inversion (TomoSAR) using multiple data stacks from different viewing angles enables us to generate 4-D (space-time) point clouds of the illuminated area from space with a point density comparable to LiDAR. They can be potentially used for facade reconstruction and deformation monitoring in urban environment. In this paper, we present the first attempt to reconstruct facades from this class of data: First, the facade region is extracted using the density estimates of the points projected to the ground plane, the extracted facade points are then clustered into individual facades by means of orientation analysis, surface (flat or curved) model parameters of the segmented building facades are further estimated, and the geometric primitives such as intersection points of the adjacent facades are determined to complete the reconstruction process. The proposed approach is illustrated and validated by examples using TomoSAR point clouds generated from stacks of TerraSAR-X high-resolution spotlight images from two viewing angles, i.e., both ascending and descending orbits. The performance of the proposed approach is systematically analyzed. To explore the possible applications, we refine the elevation estimate of each raw TomoSAR point by using its more accurate azimuth and range coordinates and the corresponding reconstructed building facade model. Compared to the raw TomoSAR point clouds, significantly improved elevation positioning accuracy is achieved. Finally, a first example of the reconstructed 4-D city model is presented. [ABSTRACT FROM PUBLISHER]

In this paper, we develop a skin-like tactile sensor array to measure the contact pressure of curved surfaces. The sensor array is laminated into a thin film 3 mm in thickness and can easily be wrapped around a pencil without damaging its skin-like structure. So far, we have achieved the array containing 8 × 16 sensor elements. Its spatial resolution is 1 element per 9 mm2 area and it can measure the pressure up to 360 kPa. The sensor-array patch contains three layers. The upper and lower layers are polydimethylsiloxane (PDMS) thin films embedded with the conductor strips formed by PDMS-based silver nanowires (AgNWs) networks. The middle layer is formed by the mixing of nickel powder with liquid PDMS for contact force measurement. Experimental tests have demonstrated that conductor strips on the upper layer can maintain their resistances ~ 23 Ω with increase when the tensile strain is up to 50%. Noted is the conductor made with carbon nanotubes can keep its conductivity unchanged for up to only 40% tensile strain. Through fatigue tests, it is observed that the measured AgNWs/PDMS conductor strip exhibits low and stable resistances. This is one of the most desired behaviors of the stretchable interconnects for signal transmission. The integrated sensor system can successfully measure the contact pressure induced by objects of different shapes. It can be applied on curved or non-planar surfaces in robots or medical devices for force detection and feedback. [ABSTRACT FROM PUBLISHER]

Many traditional two-view stereo algorithms explicitly or implicitly use the frontal parallel plane assumption when exploiting contextual information since, e.g., the smoothness prior biases toward constant disparity (depth) over a neighborhood. This introduces systematic errors to the matching process for slanted or curved surfaces. These errors are nonnegligible for detailed geometric modeling of natural objects such as a human face. We show how to use contextual information geometrically to avoid such errors. A differential geometric study of smooth surfaces allows contextual information to be encoded in Cartan's moving frame model over local quadratic approximations, providing a framework of geometric consistency for both depth and surface normals; the accuracy of our reconstructions argues for the sufficiency of the approximation. In effect, Cartan's model provides the additional constraint necessary to move beyond the frontal parallel plane assumption in stereo reconstruction. It also suggests how geometry can extend surfaces to account for unmatched points due to partial occlusion. [ABSTRACT FROM AUTHOR]

We generalize the concept of bilateral reflection symmetry to curved glide-reflection symmetry in 2D euclidean space, such that classic reflection symmetry becomes one of its six special cases. We propose a local feature-based approach for curved glide-reflection symmetry detection from real, unsegmented 2D images. Furthermore, we apply curved glide-reflection axis detection for curved reflection surface detection in 3D images. Our method discovers, groups, and connects statistically dominant local glide-reflection axes in an Axis-Parameter-Space (APS) without preassumptions on the types of reflection symmetries. Quantitative evaluations and comparisons against state-of-the-art algorithms on a diverse 64-test-image set and 1,125 Swedish leaf-data images show a promising average detection rate of the proposed algorithm at 80 and 40 percent, respectively, and superior performance over existing reflection symmetry detection algorithms. Potential applications in computer vision, particularly biomedical imaging, include saliency detection from unsegmented images and quantification of deviations from normality. We make our 64-test-image set publicly available. [ABSTRACT FROM PUBLISHER]