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Camera calibration is an essential step for the optical measurement method used in the experimental mechanics. Most plumb line methods focus on solving lens distortions without considering camera intrinsic and extrinsic parameters. In this paper, we propose a full camera calibration method to estimate the camera parameters, including camera intrinsic parameters, extrinsic parameters and lens distortion parameters, from a single image with six or more non-coplanar lines. We parameterize the 3D lines with the intersection of two planes that allow the direct linear transformation of the lines(DLT-Lines). Based on the DLT-Lines, the projection matrix is estimated linearly, and then the camera intrinsic and extrinsic parameters are extracted from the matrix. The relationship between the distorted 2D lines and the distortion coefficients is derived, based on which the distortion coefficients can be solved linearly. In the last step, a non-linear optimization algorithm is used to jointly refine all the camera parameters, including the distortion coefficients. Both synthetic and real data are used to evaluate the performance of our method, which demonstrates that the proposed method can calibrate the cameras with radial and tangential distortions accurately. We propose a DLT-lines based camera calibration method for experimental mechanics. The proposed method can calibrate all the camera parameters from a single image.

This work contributes to the generalized finite element approach in free vibration, dynamic elastic, and elastoplastic analysis of plane frame subjected to random excitation generated by the wind action. The wind velocity is modeled mathematically by using power spectral density method in combination with Shinozuka’s model, along with the commonly employed wind spectra. From these spectra, the dynamic wind loading is determined from the sum of the mean and floating wind velocities. The governing equation is formulated by Euler–Bernoulli beam theory, and it is discretized by using the enriched beam element. The enrichment is done by employing enriched finite element shape function to construct the enriched mathematical space. This strategy is constituted by the enrichment space, which is constructed by trigonometric functions, and the conventional space, which is constructed by conventional two-node Lagrange–Hermite shape function. The time increment procedure is carried out by Hilber-Hughes-Taylor algorithm and the material nonlinearity is modeled by von Mises isotropic hardening model, solved by the Newton–Raphson algorithm. A flowchart is presented to summarize the proposed numerical modeling procedure. Finally, several applications are presented, and the results obtained by the generalized finite element method are compared with those obtained by conventional beam element. Natural frequencies are determined in a one-story plane frame and are compared with reference results. The relative error in displacement is determined in h-refine strategy for quadratic beam element (FEM3), while the generalized finite element method adopts the enrichment increment strategy. The results demonstrate the competitiveness and numerical stability of generalized finite element method in this type of application. Even in comparison to the quadratic beam element, the generalized finite element method presents good performance and accuracy in numerical modeling.

Space manipulator has been playing an increasingly important role in space exploration due to its flexibility and versatility. This paper is to design a vision-based pose measurement system for a four-degree-of-freedom (4-DOF) lunar surface sampling manipulator relying on a monitoring camera and several fiducial markers. The system first employs double plateaus histogram equalization for the markers to improve the robustness to varying noise and illumination. The markers are then accurately extracted in sub-pixel based on template matching and curved surface fitting. Finally, given the camera parameters and 3D reference points, the pose of the manipulator end-effector is solved from the 3D-to-2D point correspondences by combining a plane-based pose estimation method with rigid-body transformation. Experiment results show that the system achieves high-precision positioning and orientation performance. The measurement error is within 3 mm in position, and 0.2° in orientation, meeting the requirements for space manipulator operations.

Well-defined metal nanostructures with highly tunable optical properties are promising substrates for surface-enhanced Raman scattering (SERS) research and applications. In this paper, we present a crossed junction to create plasmonic hotspot, which was fabricated by the micromanipulation of chemically synthesized silver nanowires. The field enhancements were evaluated via the detection of Raman spectra by the means of local and remote excitation, respectively. The experimental investigation and numerical simulation of dependence on polarization direction were performed. The nature of the polarization dependent enhancement is further discussed. This work would be valuable for studying properties of more complex regular nanostructure, such as 3-dimensional structures consisting of nanogaps and vertical stacking, for ultrahigh-enhancement SERS.

This paper presents a new pipeline for capturing the performance of the human body with two depth cameras in real time. Our online approach reconstructs not only the movement of the skeleton, but also the dense nonrigid 3D surface. The key to our algorithm is a coarse-to-fine strategy: large-scale deformations or rapid movements are captured by the skeleton pose tracker, with which the dense volumetric 6D motion field can be estimated robustly for dense geometry reconstruction. Shown in various sequences, our approach was able to accurately capture the 3D motion of the human body and produce increasingly denoised, detailed, and complete geometric reconstructions.

In the case of complex illumination background, the image has fuzziness and chromatic aberration, which can improve the imaging effect of the image by white balance chromatic aberration compensation. The traditional method uses the contour feature fusion adaptive matching method to compensate the white balance under the complex illumination background, which leads to the good color difference compensation effect when the image pixel is low. A white balance color compensation algorithm for fuzzy chromatic aberration based on wavelet packet decomposition is proposed. The original image was denoised and filtered. The white balance characteristics of the image were analyzed and extracted based on the wavelet packet decomposition method, and the adaptive balance design was carried out to realize the white balance and color difference compensation of the art design chromatic aberration image. By using the known pixel information of the image block to be repaired, the statistical properties of the image block to be repaired are predicted, and the matching cost of the image block to be matched that meets the restriction conditions is calculated. By introducing the objective factor, the matching cost function is improved to balance the restoration process, and the unnatural problem caused by the repeated appearance of some image details in the restoration results is solved. The simulation results show that the method can effectively balance the color difference of the image, improve the aesthetic feeling of the image, and improve the performance of the detail features of the image. The peak signal-to-noise ratio is high.

In the star images taken by the ground observatory, due to atmospheric distortion, long exposure time, and long imaging distance, some geostationary (GEO) satellite targets in the image are small in size and weak in energy. Existing methods all have troubles in dealing such cases. The paper proposes a novel GEO satellite target detection algorithm based on image transformation and energy accumulation. Firstly, the LSD line detection algorithm is used to detect the star stripe areas and eliminate them. Secondly, the star stripe is used to match the adjacent images in original images and the movement of the telescope in the vertical direction of the star stripe is eliminated via image transformation. Lastly, the energy accumulation algorithm is used to detect the location of the targets on the transformed image sequences. Experimental results on image sequences show that the proposed algorithm can effectively detect weak energy GEO satellite targets and its performance is better than the existing algorithms.

With the omnipresence of unmanned aerial vehicle (UAV), sequential aerial imagery is becoming more widely available in both civilian and military programs. Considering that the monocular imagery is sequentially ordered according to its acquisition time and a dominant ground plane is often visible in the scene, we present a novel and complete automatic Structure from Motion system based on homography constraints. The homography induced by the ground plane is used to recover the camera pose. The windowed bundle adjustment and automatic loop closure are performed in sequential reconstruction. The global bundle adjustment is performed over the complete reconstruction. The proposed SfM system has successfully been used for sequential aerial imagery taken from a UAV.

A new interleaved high step-up isolated DC-DC converter with zero-voltage switching (ZVS) is proposed in this paper. The configuration is composed of the active clamp circuits and voltage doubler circuits with parallel-input series-output structure. The active clamp circuits are used to achieve ZVS performance for the power switches such that the switching losses are reduced. The voltage doubler circuits are used to obtain high voltage gain. The voltage stresses on the power switches are greatly lower than the output voltage such that the low-voltage-rated MOSFETs with low on-resistances can be adopted to reduce the conduction losses. The input ripple current is reduced by the interleaved operation. The energy stored in leakage inductances of the coupled inductors is recycled to avoid the voltage spike on the main switches. The operating principle and steady-state analysis of the proposed converter are presented in detail. Finally, a 1000 W prototype converter with 36 V input and 380 V output is built and tested in the laboratory. The experimental results are presented to validate the feasibility and the performance of the proposed converter.

This paper presents a terahertz (THz) optical sampling technique and discusses some industrial applications in semiconductor manufacturing and failure analysis. The use of ultrashort pulse fiber lasers and specific electro-optical or opto-electrical conversion devices such as photoconductive switches enable time-domain analysis of sub-picosecond pulses, paving the way to new industrial applications.

In this paper, we propose a self-calibration approach to stereo cameras with radial distortion from stereo image pairs of a common 3D scene. Based on the epipolar constraint in the stereo image pair, the intrinsic and extrinsic parameters of stereo cameras are estimated synchronously with a minimum number of nine image point correspondences. It is significant within a random sample consensus (RANSAC) scheme to cope with the outliers of feature matches efficiently and robustly. Then the inliers of the stereo image pair that have been determined after RANSAC are used to optimize the calibration parameters of stereo cameras. Furthermore, more accurate calibration results can be achieved with the joint optimization of multiple stereo image pairs. Both synthetic and real data are used to evaluate the performance of the proposed method, demonstrating that our method can calibrate stereo cameras with radial distortions efficiently and accurately.

Flame optical tomography is an indispensable part of rocket engine tail flame diagnostic technology. This paper proposes a method for reconstructing the three-dimensional radiation field of flame by optical tomography. When using the optical tomography to measure the three-dimensional radiation field of the flame, we need to use multiple array detectors, and at the same time, we must get the projection data of the three dimensional radiation field along the same direction. In order to obtain a high resolution flame three-dimensional radiation field, we did the following work. First, we perform high-precision calibration on telecentric camera sets. Then, we ensure alignment of the two-dimensional images in multiple directions by polar line correction. Finally, we reconstruct the 3D radiation field of each layer using the 2D flame image slices. We superimpose the radiation field of each layer to reconstruct the complete high precision flame three-dimensional radiation field. We conducted experiments on flame optical chromatography. We used six cameras to shoot the experiment platform from different directions. The reprojection error of the telecentric camera group calibration result is significantly better than the total station. Finally, we obtained a high-precision flame three-dimensional radiation field. We analyzed the experimental results and summarized them at the end of the paper.

Excellent electro-optical (E-O) performances are essential for high-quality reflective cholesteric liquid crystal (LC) displays, but are often limited by the high driving voltages required by these displays. Dispersing functional nanomaterials into the LCs has emerged as a promising approach to achieve outstanding E-O properties. In this work, we report the facet-controlled E-O properties of a chiral nematic LC (N*LC) doped with cubic, octahedral, and rhombic dodecahedral Cu2O. The outstanding E-O properties of the doped systems are related to the interaction between the liquid crystals and Cu2O dopants with different exposed crystal planes. Doping with octahedral and rhombic dodecahedral Cu2O reduces the stability of the planar state, as a result of both the surface abundance of active Cu atoms that interact with the polarized LC molecules, and the large amounts of vertexes and edges on the crystal surfaces, which accelerate the transition from the planar to the focal conic state under an applied electric field. Rhombic Cu2O is the most effective dopant for improving the E-O properties of the present LCs, resulting in a 65.31% reduction of the threshold voltage. The facet and morphology effects highlighted in this work provide a new pathway to develop excellent energy-saving meso-materials with exposed high-reactivity facets, improving their potential applications in electro-optical technologies and information displays.

Infrared object tracking is a key technology in many surveillance applications. General visual tracking algorithms designed for color images can not handle infrared targets very well due to their relatively low resolutions and blurred edges. This paper presents a new tracking by detection method based on online structural learning. We show how to train the classifier efficiently with dense samples through Fourier techniques and careful implementation. Furthermore, we introduce an effective feature representation for infrared objects. Finally, we demonstrate the performance of the proposed tracker on public infrared sequences with top accuracy and robustness. Meanwhile, our single thread C++ implementation of the algorithm achieves an average tracking speed of 215 FPS on a modern cpu.

In this paper, we propose two perspective-n-line (PnL)-like methods with the presence of line detection process. Compared with the traditional methods, the proposed methods use the new error models derived from the edge points and their corresponding noisy observations rather than relying on the assumption that the noises for the two endpoints are statistically independent. Meanwhile, we improve the performance of the RAPiD-like method—another type of visual tracking approach without extracting image lines by fitting the interpolated location of the corresponding edge pixel in the local region. In addition, we compare the proposed PnL-like methods with the RAPiD-like methods and find that both the types of visual tracking methods for rigid objects are fundamentally equivalent and all of them are maximum-likelihood approaches to estimate the pose parameters, given the error model for the noisy edge points. Special consideration is put into deriving a unifying probabilistic framework to express these two types of methods. Moreover, comparisons under different performance criteria, including computational efficiency, accuracy, and robustness, are also conducted.

This paper presents a C0 quadrilateral enriched element by the Generalized Finite Element Method, having trigonometric and exponential functions as enrichment functions, applied in free vibration analysis with distorted mesh. The stiffness and mass matrices are obtained by subintervals numerical integration. The efficiency of the enriched C0 element is observed by solving several plane stress free vibrations problems. The analyses include uniform and non-uniform mesh models, and severely distorted meshes. Furthermore, the sensitivity of the enriched C0 element is also analyzed. The results of the analyses are compared with other numerical formulations and show that the enriched C0 element proposed in this paper has good performance.

In the application of displacement-relay videometrics for surface subsidence surveillance, double-sided telecentric lenses are especially suited as their constant perspective and large magnification among depth of field. As a serial camera network, it is necessary to calibrate the geometrical relationships between rigidly linked cameras in displacement-relay videometrics. Hence a calibration method for non-overlapping cameras with double-sided telecentric lenses is first proposed. The proposed method utilizes several laser planes, which can be generated by a line laser projector, as the calibration objects. The method connects the double-sided telecentric cameras using the coplanarity of laser plane which goes through the FOVs of cameras. It does not require high-precision 3D measurement equipment, but only requires an ordinary line laser projector and two plane patterns. Real data experiments are performed to validate the proposed method. The experimental results show that the given method is quite reliable and accurate, which can be used to calibrate geometrical relationships of double-sided telecentric cameras in displacement-relay videometrics.

The calibration of a camera in wide scene generally requires a large number of non-coplanar control points. This process often needs a large amount of extra auxiliary work to match the object points and the image points, and in some cases, this matching is difficult for users with insufficient experience. A feature representation and optimal priority matching method based on the angular ordered sequences (AOS) of a control point are proposed in this paper with the goal of solving the object-image auto-matching problem for control points. We also provide a strategy for dealing with the difficult situation for automatic calibration when the camera’s optical center is nearly collinear with two object points. The simulation results demonstrated that the proposed method was robust with errors for the initial value of the optical center, object points, and image points, and it could quickly achieve object-image matching for automatic calibration.

The pose of space target is a key technical parameter in navigation guidance. In launching silo, the missile pose estimation is difficult because of specific mounting location and limited field of view of cameras. To solve these problems, we design a pose measurement system which has three measurement methods based on binocular intersection, central axis and monocular camera respectively. Synthetic experiments and real image experiments show that the system is feasible and the precision of the system can meet the accuracy demand of measurement in launching silo.

PNP (Perspective-N-Point) and PNL (Perspective-N-Line) are the most commonly used methods for camera pose estimation. However, most methods are based on the hypothesis of the pinhole camera model, which ignore camera distortion’s effects. Considering the influences of camera distortion, we proposed to solve the camera pose directly by using distorted lines. In this paper, we first undistort the lines according to distortion model, then use LSD algorithm extract 2D undistorted lines from the image. Having matched 2D/3D lines, the PNL (Perspective-N-Line) was used finally to solve the camera pose. Through experiments on synthetic images and real images, it turns out that our method is effective and feasible for pose estimation.

To further extend the scope of stereo-digital image correlation (stereo-DIC) to more challenging environments, a novel Scheimpflug camera-based stereo-DIC is developed for full-field 3D deformation measurement, wherein the Scheimpflug condition, consisting of tilting the sensor plane with respect to the lens plane for the sake of larger depth of field (DOF) of the camera, is employed. The geometric imaging model of the Scheimpflug camera is described, on the basis of which a robust and effective stepwise calibration strategy is performed to calculate the intrinsic and extrinsic parameters of the stereo Scheimpflug rig. With the aid of a specially tailored stereo triangulation method and well-developed subset-based DIC algorithms, the three-dimensional shape and displacement of the specimen can be retrieved. Finally, practical experiments, including rigid motion tests and three-point bending tests, demonstrate the effectiveness and accuracy of the proposed approach.

In this paper, we propose a novel multitask learning method based on the deep convolutional network. The proposed deep network has four convolutional layers, three max-pooling layers, and two parallel fully connected layers. To adjust the deep network to multitask learning problem, we propose to learn a low-rank deep network so that the relation among different tasks can be explored. We proposed to minimize the number of independent parameter rows of one fully connected layer to explore the relations among different tasks, which is measured by the nuclear norm of the parameter of one fully connected layer, and seek a low-rank parameter matrix. Meanwhile, we also propose to regularize another fully connected layer by sparsity penalty so that the useful features learned by the lower layers can be selected. The learning problem is solved by an iterative algorithm based on gradient descent and back-propagation algorithms. The proposed algorithm is evaluated over benchmark datasets of multiple face attribute prediction, multitask natural language processing, and joint economics index predictions. The evaluation results show the advantage of the low-rank deep CNN model over multitask problems.

In the prevailing era of Internet of Things (IoT), the conventional failure analysis methodologies are more and more challenged by largely increased I/O density and data throughput with complex chip structures developed such as 3D IC and 2.5D packaging technology. Recently, impulse-based time-domain reflectometry (TDR) has gradually become a popular method to quickly localize a failure point in 2.5D/3D chip package with high resolution. However, it is still a big challenge to apply such TDR analysis for the defect characterization inside the die. In this work, a recursive modeling technique is proposed to enable the TDR analysis inside the die to the frontend-of-line (FEOL) interface.

For the problem of 3D line reconstruction in binocular or multiple view stereo vision, when there are no corresponding points on the line, the method called Direction-then-Point (DtP) can be used, and if there are two pairs of corresponding points on the line, the method called Two Points 3D coordinates (TPS) can be used. However, when there is only one pair of corresponding points on the line, can we get the better accuracy than DtP for 3D line reconstruction? In this paper, a linear and more accurate method called Point-then-Direction (PtD) is proposed. First, we used the intersection method to obtain the 3D point&rsquo, s coordinate from its corresponding image points. Then, we used this point as a position on the line to calculate the direction of the line by minimizing the image angle residual. PtD is also suitable for multiple camera systems. The simulation results demonstrate that PtD increases the accuracy of both the direction and the position of the 3D line compared to DtP. At the same time, PtD achieves a better result in direction of the 3D line than TPS, but has a lower accuracy in the position of 3D lines than TPS.

Pose estimation is important for many robotic applications including bin picking and robotic assembly and collaboration. However, robust and accurate estimation of the poses of industrial objects is a challenging task owing to the various object shapes and complex working environments. This paper presents a method of estimating the poses of narrow and elongated industrial objects with a low-cost RGB-D (depth and color) camera to guide the process of robotic assembly. The proposed method comprises three main steps: reconstruction involved in preprocessing, pose initialization with geometric features, and tracking aided by contour cues. Pose tracking is coupled with real-time dense reconstruction, which can synthesize a smooth depth image as a substitute for the raw depth image. Because industrial objects (e.g., fork and adapter) feature mostly planar structures, primitive geometric features, such as three-dimensional planes, are extracted from the point cloud and utilized to induce a promising initial pose. For robust tracking of the adapter consisting of narrow and elongated planes, the dense surface correspondences are combined with sparse contour correspondences in the refinement scheme. This combination allows for a satisfactory tolerance to the initial guess in the pose tracking phase. The experimental results demonstrate the feasibility of the proposed method.

Development of lithium ion batteries with ultrafast charging rate as well as high energy/power densities and long cycle-life is one of the imperative works in the field of batteries. To achieve this goal, it requires not only to develop new electrode materials but also to develop nano-characterization techniques that are capable of investigating the dynamic evolution of the surface/interface morphology and property of fast charging electrode materials during battery operation. Although electrochemical atomic force microscopy (EC-AFM) holds high spatial resolution, its imaging speed is too slow to visualize dynamics occurring on the timescale of minutes. In this article, we present an electrochemical high-speed AFM (EC-HS-AFM), developed by addressing key technologies involving optical detection of small cantilever deflection, dual scanner capable of high-speed and wide-range imaging, and electrochemical cell with three electrodes. EC-HS-AFM imaging from 1 fpm to ∼1 fps with a maximum scan range of 40 × 40 µm2 has been stably and reliably realized. Dynamic morphological changes in the LiMn2O4 nanoparticles during cyclic voltammetry measurements in the 0.5 mol/l Li2SO4 solution were successfully visualized. This technique will provide the possibility of tracking dynamic processes of fast charging battery materials and other surface/interface processes such as the formation of the solid electrolyte interphase layer.

To enhance the electrochemical performance of MXene-based materials for energy storage devices, the componential modification related to the electrode capacity and the structural engineering related to the electrode stability are general strategies. Herein, a well-designed three-dimensional (3D) MXene-based aerogel (NiCo2-LDHs@MXene/rGO) on composition and structure is constructed by integrating MXene, NiCo2-LDHs, and reduced graphene oxide via a two-step method including hydrothermal and wet chemical techniques. This aerogel exhibits ultra-light nature, high theoretical capacity of LDHs, unblocked ion/electron channels of hierarchical structure, and good electrical conductivity of MXene and rGO networks, contributing to outstanding energy and power density, favorable capacity loss, and excellent stability as battery-type cathode material for supercapacitor. Most importantly, this aerogel delivers a remarkable specific capacity of 332.2 mAh g−1 at 1 A g−1 and a good durability of 87.5% after 5000 cycles at 5 A g−1 in a three-electrode system. Furthermore, a typical hybrid supercapacitor (HSC) device fabricated with NiCo2-LDHs@MXene/rGO as the cathode and MXene/rGO as the anode (NiCo2-LDHs@MXene/rGO//MXene/rGO) provides a superior energy density of 65.3 Wh kg−1 at a power density of 700 W kg−1, and maintains the capacity retention rate of 92.8% after 10,000 cycles at 5 A g−1. This work supplies a promising strategy to prepare MXene-based electrodes for assembling high-performance and low-cost energy storage devices.

3D metrology of a stereovision system requires epipolar rectification to be performed before dense stereo matching. In this study, we propose an epipolar rectification method for a stereovision system with two telecentric lens-based cameras. Given the orthographic projection matrices of each camera, the new projection matrices are computed by determining the new camera coordinates system in affine space and imposing some constraints on the intrinsic parameters. Then, the transformation that maps the old image planes on to the new image planes is achieved. Experiments are performed to validate the performance of the proposed rectification method. The test results show that the perpendicular distance and 3D reconstructed deviation obtained from the rectified images is not significantly higher than the corresponding values obtained from the original images. Considering the roughness of the extracted corner points and calibrated camera parameters, we can conclude that the proposed method can provide sufficiently accurate rectification results.

This work proposes a methodology for defective pipe elastoplastic analysis using the Euler Bernoulli beam-pipe element formulation. The virtual work equation is modified to incorporate the stress concentration factor in beam-pipe element formulation. The stress concentration factor is evaluated a priori by a 2D or 3D finite element model according to the defect profile. In this work, a semicircular defect and a rectangular defect are considered. The stress concentration factor is inserted into the beam-pipe element elastoplastic formulation, and several applications are presented to show the applicability of the proposed method.

High output power density millimeter-wave (mm-wave) signal sources are demonstrated at 60 and 140 GHz by a magnetic plasmon waveguide (MPW) based in-phase coupled oscillator network (CON) in 65-nm CMOS. Each oscillator unit-cell is designed by an MPW-based low-loss inter-digital zero-phase coupler (ZPC). With multiple in-phase coupled ZPC unit-cells, a high output power mm-wave signal is generated at the center of the CON by an in-phase power combination. A 60-GHz CON-based signal source is implemented with four in-phase CON unit-cells at 60 GHz in a compact core chip area of ${\text {0.11 mm}}^{2}$ . It is measured with 2-mW peak differential output power, 2.2% power efficiency, ${\text {18.2-mW/mm}}^{2}$ output power density, $-{\text {113.9-dBc/Hz}}$ phase noise at 10-MHz offset, and 15.8% frequency tuning range (FTR) centered at 63.1 GHz. Moreover, a 140-GHz signal source is implemented by the combination of second-order harmonics of four in-phase coupled ZPC unit-cells at 70 GHz in a compact core chip area of ${\text {0.13 mm}}^{2}$ . It is measured with 3.5-mW peak output power, 2.4% power efficiency, ${\text {26.9-mW/mm}}^{2}$ output power density, $-{\text {104.9-dBc/Hz}}$ phase noise at 25-MHz offset, and 9.7% FTR centered at 133.5 GHz.

This paper proposes a homograhpy estimation algorithm that uses contour model to track and locate the texture-less object in high clutter environments. The proposed method consists of a homography recognition with the correspondences between model and image lines unknown, followed by a nonlinear homography optimization based on the maximum likelihood criterion. In our approach, the initial estimation of the homography is obtained in the framework of RANSAC-like, which contains two stages: hypothesizing and verifying. The first stage generates a number of homograhpy hypotheses from the correspondences of the quadrangle-like structures. Next, the homography hypotheses are quickly ranked according to a redefined distance function. In the refinement procedure, the model sample points are projected into the image plane. After that, 1D search is utilized along the normal direction to obtain the corresponding image point for each model sample point. Finally, the optimized homography is obtained by minimizing the errors between the sample points and their corresponding image points. Experiments show that the proposed method performs robust homography recognition of texture-less planar objects and maintains accurate and stable homography estimation in the cluttered environments as well as the cases of extreme slant angles. We proposed an effective homography recognition based on quadrangle-like structures.We derived a new distance function between lines in the probabilistic criterion.We presented a robust homography optimization without image contour extraction.We solved the nonlinear homography refinement by the maximum likelihood approach.

In this study, the authors have proposed a new solution for the problem of pose estimation from a set of matched 3D model and 2D image lines. Traditional line-based pose estimation methods utilising the finite information of the observations are based on the assumption that the noises for the two endpoints of the image line segment are statistically independent. However, in this study, the authors prove that these two noises are negatively correlative when the image line segment is fitted by the least-squares technique from the noisy edge points. Moreover, the authors derive the noise model describing the probabilistic relationship between the 3D model line and their finite image observations. Based on the proposed noise model, the maximum-likelihood approach is exploited to estimate the pose parameters. The authors have carried out synthetic experiments to compare the proposed method to other pose optimisation methods in the literature. The experimental results show that the proposed methods yield a clear higher precision than the traditional methods. The authors also use real image sequences to demonstrate the performance of the proposed method.

A ship horizontal attitude estimation approach with horizon tracking has been proposed, which consists of four steps. First, the approximate parameters of the horizon in successive frames are predicted. Then the candidate edges are achieved by defining a small region of interest (ROI) around the predicted horizon location, and the final horizon is acquired according to the statistic appearance of the local region. Third, the optimal camera attitude is updated based on the horizon with the designed Kalman filter. Finally, the ship horizontal attitude is obtained according to the installation azimuth of the camera. As processing in a local region, the horizon detection process takes a short time and performs robust to the false alarms. Compared with the traditional attitude determining method based on horizon for unmanned aerial vehicle (UAV), the ship horizontal attitude is achieved with the camera's installation azimuth. In order to test the performance of the proposed approach, the experiments are performed based on the videos captured by the camera which is fixed on the ship board. The experimental results indicate that the estimation accuracy of the horizontal attitude can be achieved at 10″ (1 σ ) in pitch angle at a speed of 20 fps.

In this paper, a compact fractional-order equivalent circuit model is developed to characterize three types of metamaterial transmission lines (T-lines): 1) composite right-/left-handed transmission line T-line; 2) split ring resonator T-line; and 3) complimentary split ring resonator T-line, all designed in 65-nm CMOS process at millimeter-wave frequency region. With the consideration of frequency-dependent dispersion loss and nonquasistatic effect, the proposed fractional-order equivalent circuit model can compactly characterize the measured results with good agreement up to 325 GHz.

Estimating and tracking the pose of objects is a key task in the field of photogrammetry and computer vision, playing an important role in a large number of applications and is receiving significant attentions. Combining CAD model and images from monocular RGB camera to estimate and track the pose of 3D objects has lots of applications. Despite enormous approaches exist, a deep review of the literatures on 3D pose estimation and tracking is still lacking. The paper reviews the works on model-based 3D objects pose estimation and tracking during the past two decades and classifies the approaches into different categories.

Structural SVM trackers and correlation filter trackers have demonstrated dominant performance in recent object tracking benchmarks. However, structural SVM trackers naturally suffer from shortage of samples and low speed, and time-consuming adaption is need to relieve the correlation filter trackers from boundary effects. Thus, we design a jointed tracker by concatenating a high-speed SSVM method-DSLT and a multi feature CF method-STAPLE to realize advantage complementation. We show that the tracking precision and robustness can be improve by a large margin comparing to either single tracker with little sacrifice of speed.

Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) are life-threatening disease. However, there are only few epidemiologic studies of SJS/TEN from China. To analyze the clinical characteristics, causality, and outcome of treatment for SJS/TEN in China, we reviewed case reports of patients with SJS/TEN from the China National Knowledge Infrastructure (CNKI) and Wanfang database from 2006 to 2016 and patients with SJS/TEN who were admitted to the First Affiliated Hospital of Fujian Medical University during the same period. There were 166 patients enrolled, including 70 SJS, 2 SJS/TEN overlap, and 94 TEN. The most common offending drugs were antibiotics (29.5%) and anticonvulsants (24.1%). Carbamazepine, allopurinol, and penicillins were the most common single offending drugs (17.5%, 9.6%, and 7.2%). Chinese patent medicines accounted for 5.4%. There were 76 (45.8%) patients receiving systemic steroid and intravenous immunoglobulin (IVIG) in combination therapy, especially for TEN (80.3%), and others were treated with systemic steroids alone. Mortality rate of combination treatment comparing with steroid alone in TEN patients had no statistical significance. In conclusion, carbamazepine and allopurinol were the leading causative drugs for SJS/TEN in China. Combination of IVIG and steroids is a common treatment for TEN, but its efficacy in improving mortality needs further investigation.

In this paper, we exploit prior information from global positioning systems and inertial measurement units to speed up the process of large scene reconstruction from images acquired by Unmanned Aerial Vehicles. We utilize weak pose information and intrinsic parameter to obtain the projection matrix for each view. As compared to unmanned aerial vehicles' flight altitude, topographic relief can usually be ignored, we assume that the scene is flat and use weak perspective camera to get projective transformations between two views. Furthermore, we propose an overlap criterion and select potentially matching view pairs between projective transformed views. A robust global structure from motion method is used for image based reconstruction. Our real world experiments show that the approach is accurate, scalable and computationally efficient. Moreover, projective transformations between views can also be used to eliminate false matching.

As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this paper, a new circular coded target designed by RockeTech technology Corp. Ltd is analyzed and studied, which is called circular coded diagonal target (CCDT). A novel detection and recognition method with good robustness is proposed in the paper, and implemented on Visual Studio. In this algorithm, firstly, the ellipse features of the center circle are used for rough positioning. Then, according to the characteristics of the center diagonal target, a circular frequency filter is designed to choose the correct center circle and eliminates non-target noise. The precise positioning of the coded target is done by the correlation coefficient fitting extreme value method. Finally, the coded target recognition is achieved by decoding the binary sequence in the outer ring of the extracted target. To test the proposed algorithm, this paper has carried out simulation experiments and real experiments. The results show that the CCDT recognition and accurate locating method proposed in this paper can robustly recognize and accurately locate the targets in complex and noisy background.

The bearing only tracking problem is to measure the position and velocity of moving points from a moving camera. The method in this paper mainly solves the measurement problem of a single camera or some non-synchronized cameras. This paper introduces the process model and basic method of bearing only tracking problem, and the different optimization methods based on it, then compares the advantages and disadvantages of those optimization methods. The research method of this kind of problem is discussed in the last of this paper.

The paper aims to challenge non-GPS navigation problems by using visual sensors and geo-referenced images. An area-based method is proposed to estimate full navigation parameters (FNPs), including attitude, altitude and horizontal position, for unmanned aerial vehicle (UAV) navigation. Our method is composed of three main modules: geometric transfer function, local normalized sobel energy image (LNSEI) based objective function and simplex-simulated annealing (SSA) based optimization algorithm. The adoption of relatively rich scene information and LNSEI, makes it possible to yield a solution robustly even in the presence of very noisy cases, such as multi-modal and/or multi-temporal images that differ in the type of visual sensor, season, illumination, weather, and so on, and also to handle the sparsely textured regions where features are barely detected or matched. Simulation experiments using many synthetic images clearly support noise resistance and estimation accuracy, and experimental results using 2367 real images show the maximum estimation error of 5.16 (meter) for horizontal position, 9.72 (meter) for altitude and 0.82 (degree) for attitude.

A frequency-spatial domain based model for salient region detection was proposed. The paper gives a thorough theoretical analysis of detecting salient gradients belong to salient region in the frequency domain. The model detects and highlights salient gradient changes in the frequency domain firstly; then the image is segmented into regions in the spatial domain, and the salient gradients detection and segment results are fused using a probabilistic framework to produce the full resolution, region-wise saliency map. It was demonstrated that this model has the ability to detect salient regions accurately and highlight them uniformly. A publically available benchmark was used to demonstrate that the model outperformed state-of-the-art algorithms when identifying the salient regions where greater attention should be paid by human observers.

High-sensitivity super-regenerative receivers (SRXs) are demonstrated at 96 and 135 GHz, respectively, in this paper. They are based on high-Q quench-controlled metamaterial resonators with a differential transmission line loaded with a split-ring resonator (DTL-SRR) and a differential transmission line loaded with a complementary split-ring resonator (DTL-CSRR) in 65-nm CMOS. High-Q oscillatory amplifications are established by the sharp stopband introduced by metamaterial resonators. As such, high detection sensitivity is achieved for SRXs at millimeter-wave regions. The fabricated 96-GHz DTL-CSRR-based SRX has a compact core chip area of 0.014 mm 2 with measured power consumption of 2.8 mW, sensitivity of -79 dBm, noise figure (NF) of 8.5 dB, and noise equivalent power (NEP) of 0.67 fW/√(Hz). The fabricated 135-GHz DTL-SRR-based SRX has a compact core chip area of 0.0085 mm 2 with measured power consumption of 6.2 mW, sensitivity of -76.8 dBm, NF of 9.7 dB, and NEP of 0.9 fW/√(Hz). Compared to the conventional SRX with an LC-tank-based resonator at similar frequencies, the proposed SRXs have 2.8~4 dB sensitivity improvement and 60% smaller area. The integrated SRXs are also demonstrated for the imaging applications.