Search

Event location in power systems is quite essential information for system operators to enhance control-room situational awareness capability. Therefore, it is of great importance to develop an event location estimation algorithm for transmission systems with high accuracy. With the development of wide-area measurement system (WAMS) such as FNET/GridEye, and the synchrophasor measurement devices (SMDs) such as frequency disturbance recorders (FDRs), the synchronous measurement data including frequency, voltage amplitude and phase angle can be collected and used for event location estimation. First, the phase angle and rate of change of frequency (RoCoF) trajectories are respectively used for determining two sets of wave arrival time associated with each FDR. Then, a convolutional neural network (CNN) is utilized to determine the wave arrival order to select the more suitable set of wave arrival times for a given case and to perform corresponding modifications. Next, the oscillation intensity associated with each FDR is determined based on phase angle trajectories in the center of inertia (COI) coordinate system. Finally, the multiple criteria for event location estimation are represented. Case studies and comparisons between the proposed and previous algorithms using actual and confirmed cases in U.S. power systems are performed to demonstrate the effectiveness and improvement of the proposed algorithm in practical applications. [ABSTRACT FROM AUTHOR]

Active three-dimensional(3-D) thermography combines 3-D shape and active thermography. Thus, it enables the provision of the intuitive thermographic inspection results for composite parts with a complex geometry. However, conventional 3-D thermography acquires thermographic information and 3-D shape through at least two independent sensors and requires complex cross-modal image registration algorithm based on the keypoint detection and matching. In this article, an active 3-D thermography system is proposed using only one thermal camera for moving objects. This system does not require an independent 3-D sensor while the thermal camera acts as the 3-D sensor. Nature behind that is that a mathematical model is proposed to unify the line scanning thermography and laser triangulation in the dynamic scanning process, taking a line laser as both heat excitation for active thermography and spatial coding for 3-D reconstruction. Furthermore, the model enables the feature-free registration of thermogram sequence and 3-D shape, so that the registration is fast and robust without keypoint features. The experiments on standard height specimens, 3-D printing glass fiber composites, and carbon fiber intake tube have shown the error is calibrated within 0.25 mm in the range of 1 to 150 mm and evidenced the capability for subsurface defects detection. The ease and robustness of the proposed active 3-D thermography have a bright future for 3-D measurement, defects detection, and quality control in the production line. [ABSTRACT FROM AUTHOR]

In this paper, a simultaneous localization and mapping (SLAM) method that eliminates the influence of moving objects in dynamic environments is proposed. This method utilizes the correlation between map points to separate points that are part of the static scene and points that are part of different moving objects into different groups. A sparse graph is first created using Delaunay triangulation from all map points. In this graph, the vertices represent map points, and each edge represents the correlation between adjacent points. If the relative position between two points remains consistent over time, there is correlation between them, and they are considered to be moving together rigidly. If not, they are considered to have no correlation and to be in separate groups. After the edges between the uncorrelated points are removed during point-correlation optimization, the remaining graph separates the map points of the moving objects from the map points of the static scene. The largest group is assumed to be the group of reliable static map points. Finally, motion estimation is performed using only these points. The proposed method was implemented for RGB-D sensors, evaluated with a public RGB-D benchmark, and tested in several additional challenging environments. The experimental results demonstrate that robust and accurate performance can be achieved by the proposed SLAM method in both slightly and highly dynamic environments. Compared with other state-of-the-art methods, the proposed method can provide competitive accuracy with good real-time performance. [ABSTRACT FROM AUTHOR]

Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. The proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches. [ABSTRACT FROM AUTHOR]

When organizing robots into formations, the interplay between the underlying network topology of the team and the sensing and communication modalities available to the individual robots has a fundamental effect on what types of formations are possible. The purpose of this article is to characterize the available motions of formations in which relative angles between robots equipped with bearing-only sensors are maintained. First, infinitesimal shape-similarity, a property of frameworks for which maintaining certain angles between robots ensures that the formation is invariant to translation, rotation, and uniform scaling, is examined; the shape-similarity matrix is redeveloped, and results on its nullspace are presented. Second, triangulations, a class of frameworks, are shown to be infinitesimally shape-similar. Finally, the coupling between network topology and robot capabilities is examined through the design of a decentralized heterogeneous formation-control strategy for a class of triangulations in which all robots are equipped with bearing-only sensors and a single robot can measure distances; the formation-control strategy is demonstrated on a team of differential-drive robots. [ABSTRACT FROM AUTHOR]

Layout migration is a fast methodology to generate the required layout for given circuits with different device attributes or different technology. By keeping the original layout topology, the previous design experience can help to keep the circuit performance. However, routing preservation is often not mentioned in previous layout migration techniques, which requires a complete rerouting to break the original style. Pan et al. (2015) proposed a topological slicing tree and a constrained delaunay triangulation (CDT) model to keep the routing style during migration. However, this approach may incur some missing nets after migration, which still requires tedious manual works to fix those nets. In this article, we propose a sequence pair (SP)-based placement migration methodology and a novel Cartesian detection line (CDL) model to preserve the routing styles in original layouts. By using the proposed approach, the routability information and routing behaviors can be preserved during layout migration. In order to prevent from missing nets, several refinement techniques are also proposed to fix unreasonable routing nets due to block displacement. In the experiments, the missing nets after migration can be reduced to almost zero with the proposed CDL model, which greatly reduces the extra design efforts. [ABSTRACT FROM AUTHOR]

Objective: In this study, we have used whole heart simulations parameterized with large animal experiments to validate three techniques (two from the literature and one novel) for estimating epicardial and volumetric conduction velocity (CV). Methods: We used an eikonal-based simulation model to generate ground truth activation sequences with prescribed CVs. Using the sampling density achieved experimentally we examined the accuracy with which we could reconstruct the wavefront, and then examined the robustness of three CV estimation techniques to reconstruction related error. We examined a triangulation-based, inverse-gradient-based, and streamline-based techniques for estimating CV cross the surface and within the volume of the heart. Results: The reconstructed activation times agreed closely with simulated values, with 50-70% of the volumetric nodes and 97-99% of the epicardial nodes were within 1 ms of the ground truth. We found close agreement between the CVs calculated using reconstructed versus ground truth activation times, with differences in the median estimated CV on the order of 3-5% volumetrically and 1-2% superficially, regardless of what technique was used. Conclusion: Our results indicate that the wavefront reconstruction and CV estimation techniques are accurate, allowing us to examine changes in propagation induced by experimental interventions such as acute ischemia, ectopic pacing, or drugs. Significance: We implemented, validated, and compared the performance of a number of CV estimation techniques. The CV estimation techniques implemented in this study produce accurate, high-resolution CV fields that can be used to study propagation in the heart experimentally and clinically. [ABSTRACT FROM AUTHOR]

We present supervision by registration and triangulation (SRT), an unsupervised approach that utilizes unlabeled multi-view video to improve the accuracy and precision of landmark detectors. Being able to utilize unlabeled data enables our detectors to learn from massive amounts of unlabeled data freely available and not be limited by the quality and quantity of manual human annotations. To utilize unlabeled data, there are two key observations: (I) The detections of the same landmark in adjacent frames should be coherent with registration, i.e., optical flow. (II) The detections of the same landmark in multiple synchronized and geometrically calibrated views should correspond to a single 3D point, i.e., multi-view consistency. Registration and multi-view consistency are sources of supervision that do not require manual labeling, thus it can be leveraged to augment existing training data during detector training. End-to-end training is made possible by differentiable registration and 3D triangulation modules. Experiments with 11 datasets and a newly proposed metric to measure precision demonstrate accuracy and precision improvements in landmark detection on both images and video. [ABSTRACT FROM AUTHOR]

A low-frequency angular acceleration rotary table (LFAART) is capable of sinusoidal motion around a fixed position and essential to verify dynamic characteristics of a gyroscope device. The table’s performance at different swinging frequencies and amplitudes needs to be calibrated to realize traceability. However, there has been little research on the LFAART calibration. Besides, the existing measurement methods of sinusoidal angular motion parameters are not adequate for the needs of the LFAART calibration in terms of measurement range, precision, and feasibility. This article presents a calibration scheme combining an optical shaft encoder and a laser triangulation sensor. When the rotation amplitude covers sufficient slots of the scale grating, the optical shaft encoder is applied, while the laser triangulation sensor is used for a tiny amplitude motion. An algorithm is proposed to accurately calculate the angular acceleration amplitude and frequency of the rotation utilizing sinusoidal phase-modulated signals of the optical shaft encoder output. Singular zero-crossings of the series are discarded, and intervals of reversing moments are recognized according to the signal derivative’s sign at remaining zero-crossings. Then intervals are divided into subintervals to obtain accurate reversing moments. Finally, angular displacements between two adjacent reversing moments are estimated based on the fringe counting method, and the amplitude and frequency are calculated. The measurement uncertainty analysis and experiment demonstrate that the calibration scheme, including the algorithm, possesses high accuracy and resolution, wide range, and good operability, which perfectly solves the rotation’s angular acceleration amplitude and frequency. [ABSTRACT FROM AUTHOR]

On-machine measurement (OMM) is increasingly used to inspect freeform surfaces without unloading the workpiece from the machine tool. Compared to the mechanical probe deployed in many OMM processes, a laser displacement sensor has its advantage of high scanning efficiency. However, the accuracy has been a bottleneck limiting its application in precision inspection, due to the lack of a rigorously planned path. In this work, an error compensation model is established and verified considering laser triangulation error, misalignment from calibration, tooling error, and preevaluated error. Essentially, error modeling contributes to improve the measurement accuracy of laser triangulation OMM (LTOMM). After understanding these errors, a reliable measuring path is crucial to maintain the given accuracy of LTOMM. This path generated is capable of minimizing the measurement time at a given accuracy constraint. In a particular case study, a turbine blade surface was inspected using LTOMM following generated path against a built-in probe. The measurement time was reduced by 77.4% for a constraining accuracy of $\pm 10~\mu \text{m}$. The time could be further reduced by 38.6%, for a constraining accuracy of $\pm 13~\mu \text{m}$. This study has demonstrated that LTOMM could potentially replace the on-machine probe during measurement of freeform surfaces, toward more efficient industrial applications in the future. [ABSTRACT FROM AUTHOR]

With the aims of safe, smart and sustainable future mobility, a personalized approach of trajectory planning and control based on user preferences is developed for lane-change of autonomous vehicles in this paper. First, a safe area during the lane change process is identified by using constraint Delaunay triangulation. Then, an improved rapidly-exploring Random Trees (i-RRT) is developed with B-spline to generate the feasible trajectory cluster, which is subject to the safe area boundaries and the vehicle dynamics. To extract a personalized trajectory from this cluster, we firstly adopt the fuzzy linguistic preference relation (FLPR) method to identify users’ preferences on driving, which can be reflected by their subjective objectives including driving safety, ride comfort and vehicle stability. Then, the technique for order preference by similarity to ideal situation (TOPSIS) is utilized to solve the multi-objective optimisation problem formulated by considering the user preferences. The algorithms proposed above are integrated, and both simulation and experimental validation are conducted under lane-change scenarios of autonomous driving. Simulation and experiment results show that proposed approach is able to successfully realize personalized trajectory planning and lane-change control, satisfying users’ various preferences and simultaneously ensure vehicle safety, demonstrating its feasibility and effectiveness. [ABSTRACT FROM AUTHOR]

Most 3-D laser scanners are based on 3-D optical triangulation algorithms, where the location of each 3-D point is estimated as the intersection of a camera ray and a plane of light projected by a laser line generator. Since a physical laser-line generator projects a sheet of light of finite thickness, inaccurate measurements and errors result from assuming that the plane of light is infinitesimally thin. We propose a new mathematical formulation for 3-D optical triangulation based on interval arithmetic, where 3-D points are only determined within certain bounds along the camera rays, and multiple measurements are used to tighten these bounds. We propose the line segment cloud as an alternative surface representation to visualize the measurement errors within the proposed framework. We introduce the iterative line segment tightening algorithm to convert line segment clouds into point clouds, as a preprocessing step prior to surface reconstruction. We describe how to construct a low-cost laser-line 3-D scanner, where the camera is fixed with respect to the object and the laser-line generator is mounted on a high-resolution motion platform. We describe a GPU-based implementation where the large number of captured images is processed in real time. Finally, we present some experimental results. [ABSTRACT FROM AUTHOR]

We study the accuracy of triangulation in multi-camera systems with respect to the number of cameras. We show that, under certain conditions, the optimal achievable reconstruction error decays quadratically as more cameras are added to the system. Furthermore, we analyze the error decay-rate of major state-of-the-art algorithms with respect to the number of cameras. To this end, we introduce the notion of consistency for triangulation, and show that consistent reconstruction algorithms achieve the optimal quadratic decay, which is asymptotically faster than some other methods. Finally, we present simulations results supporting our findings. Our simulations have been implemented in MATLAB and the resulting code is available in the supplementary material, which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TPAMI.2019.2939530. [ABSTRACT FROM AUTHOR]

Visible light positioning systems (VLPSs) are a feasible alternative to local positioning systems due to the technology improvement and massive use of light-emitting diodes (LEDs). Compared to other technologies, VLPSs can provide significant advantages, such as the achieved accuracy, although they still present some issues, mainly related to the reduced coverage area or the high computational load. This article proposes the design of a VLPS based on four LED lamps as transmitters and a quadrant photodiode angular diversity aperture (QADA) as a receiver. As the shape of the QADA is circular and the aperture to be installed over it is square, we derive the corresponding general equations to obtain the currents through the different pads of the QADA, regarding the angle of incidence of the light (and, inversely, how to estimate the angle of incidence from the measured currents). An encoding scheme based on 1023-bit Kasami sequences is proposed for every transmission from the LED lamps, thus providing multiple access capability and robustness against low signal-to-noise ratios and harsh conditions, such as multipath and near-far effect. A triangulation technique has been applied to estimate the receiver’s position, by means of the least-squares estimator (LSE), together with some geometrical considerations. The proposal has been validated by simulation and by experimental tests, obtaining 3-D positioning average errors below 13 and 5.5 cm for separations between the transmitters’ plane and the receiver of 2 and 1 m, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we present an approach to local coverage path (CP) planning for a circular mobile sensor. Our family of algorithms provides completed and overlapped coverage control, curvature and path length control, localization, choice of observer’s placement based on sensing range, and first-order differentiable CP. Our family of algorithms begins by partitioning the target region (TR) into several regular triangulations (RTs). Based on the size of the RT and the sensing range, the number and location of observers are determined for all RT. All observers found are then used as waypoints (WPs) to generate baseline CP with the Traveling Salesman Problem’s nearest neighbor algorithm. The proposed algorithm solved the problems of how to design a differentiable and collision-free CP for all sensing range, limited and sufficient, while providing completed coverage control, overlapped coverage control, curvature and path length control, localization, collision avoidance, and the choice of observer’s placement based on sensing range and the environment. The main technical contributions of the proposed approach is to provide a holistic solution that segments any TR, uses triangulation to determine the observation WPs and then compute the smooth and collision-free CP. Computer simulations are provided to validate the effectiveness and correctness of our algorithms. [ABSTRACT FROM AUTHOR]

In scan-based 3-D systems, the achievable measurement time is strongly restrained by the moving mass. This limitation can be relaxed, by scanning the optical path instead of moving the entire sensor, such that a higher measurement speed can be achieved. This article deals with the design, the control, and the measurement results of a scanning triangulation sensor, in which the illumination and reflection paths of the sensor are scanned by a fast steering mirror (FSM). The system architecture is determined using ray-tracing simulations, such that the performance of the scanning system can be determined in advance. To scan the area of interest with the FSM, conventional raster trajectories and Lissajous trajectories are employed, which provide an early overview of the scan area. For tracking these trajectories, PID and dual-tone controllers are used, respectively. The experimental results demonstrate that for both scan trajectories, the sample can be captured correctly, with a frame rate of 1 frame/s, a maximum spatial resolution of 130 $\mu \text{m}$ , and a field of view of $11.5\,\,\times 18.5\,\,{\mathrm{ mm}}^{2}$. [ABSTRACT FROM AUTHOR]

This paper presents a cost-effective localization method by using received signal strength (RSS) from single wireless access point (AP) that has only three directional antennas. To reduce the requirement for the costly database training process, a three-step parametric model-based approach is proposed. This approach estimates the AP-device angle, distance, and the device location analytically by making use of wireless path-loss models, antenna radiation patterns, and differential RSS. Meanwhile, the differential antenna gain is introduced to eliminate the need for known AP-device distances when estimating the AP-device angle. Furthermore, to circumvent the difficulty in detecting outliers in a single-AP system, this paper further integrates single-AP solutions with dead-reckoning (DR) to obtain more robust solutions. Three types of measurement models (i.e., the device location updates, AP-device angle updates, and AP-device distance updates) are built from the single-AP localization system. Static and dynamic field tests with the new Bluetooth 5 signals indicated the possibility for using RSS from three directional antennas on single AP to obtain a low-cost localization solution and the effectiveness of integrating with DR on mitigating the impact of outliers. [ABSTRACT FROM AUTHOR]

A structured light system is used to position a scientific instrument mounted on a Mars rover robotic arm relative to a Mars surface sample. Fifty laser spots are projected on the Mars surface sample. The identification of individual laser spots, the centroiding algorithm, and the calibration are discussed. Results show that the system measures the distance to the Mars surface sample more accurate than 50 μm at a nominal operating distance of 30 mm. [ABSTRACT FROM AUTHOR]

In situ visualization of laparoscopic ultrasound in both conventional and robot-assisted laparoscopic surgery requires robust and efficient computation of the pose of the laparoscopic ultrasound probe with respect to the laparoscopic camera. Image-based intrinsic methods of computing this relative pose need to overcome challenges due to irregular illumination, partial feature occlusion, and clutter that are unavoidable in practical laparoscopic surgery. In this paper, we propose an accurate image-based method that is robust to partial occlusion of the fiducials and outliers. The method is extended to multi-view imaging model with applications in stereoscopic laparoscopy and robot-assisted surgery. Rather than treating the model-to-image correspondence and pose computation as separate problems, we solve them jointly using the Kalman Filter-based framework that demonstrates video rate running time (~24fps). By keeping the optical tracking measurements as a reference, we demonstrate that the proposed methods result in clinically acceptable tracking accuracy, reaching target registration errors well below 1.5mm on average. In addition, our multi-view tracking method is compared to a conventional stereo triangulation-based pose estimation scheme that commercial optical tracking systems are based on, to experimentally demonstrate its superiority in terms of accuracy. Finally, we qualitatively demonstrate the suitability of our methods for practical laparoscopic applications by conducting a phantom-based experiment. [ABSTRACT FROM AUTHOR]

Multiple-view triangulation by $\ell _\infty$ minimisation has become established in computer vision. State-of-the-art $\ell _\infty$ triangulation algorithms exploit the quasiconvexity of the cost function to derive iterative update rules that deliver the global minimum. Such algorithms, however, can be computationally costly for large problem instances that contain many image measurements, e.g., from web-based photo sharing sites or long-term video recordings. In this paper, we prove that $\ell _\infty$ triangulation admits a coreset approximation scheme, which seeks small representative subsets of the input data called coresets. A coreset possesses the special property that the error of the $\ell _\infty$ solution on the coreset is within known bounds from the global minimum. We establish the necessary mathematical underpinnings of the coreset algorithm, specifically, by enacting the stopping criterion of the algorithm and proving that the resulting coreset gives the desired approximation accuracy. On large-scale triangulation problems, our method provides theoretically sound approximate solutions. Iterated until convergence, our coreset algorithm is also guaranteed to reach the true optimum. On practical datasets, we show that our technique can in fact attain the global minimiser much faster than current methods. [ABSTRACT FROM AUTHOR]

Design of contemporary antenna structures is heavily based on full-wave electromagnetic (EM) simulation tools. They provide accuracy but are CPU intensive. Reduction of EM-driven design procedure cost can be achieved by using fast replacement models (surrogates). Unfortunately, standard modeling techniques are unable to ensure sufficient predictive power for real-world antenna structures (multiple parameters, wide parameter ranges, and highly nonlinear responses). Here, a design-oriented modeling technique is introduced, in which the most critical part is the domain definition. The surrogate is constructed in the region based on a set of reference designs, optimized with respect to user-selected figures of interest such as operating frequencies, bandwidth, and substrate permittivity. The domain is spanned by the simplexes, obtained by triangulation of the reference designs, further extended into their orthogonal complements. Restricting the model domain as above permits dramatic reduction of the number of training data samples necessary to build a reliable model, as compared to the conventional approach. The proposed modeling framework is demonstrated using three examples, a UWB monopole, and two dual-band antennas. Comprehensive benchmarking as well as application studies and experimental verification are also provided. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a coverage path (CP) planning approach for a mobile robot moving in a dynamically changing environment. Our family of algorithms begins by finding the first path around the center of interior obstacles/disks of a given target region (TR) through the Graham scan algorithm. The first path is then used as a foundational path to generate a collision free, first order differentiable, and observable CP through a complete set of input and output transformation algorithms which together form the rainbow CP planning approach. The last algorithm of the rainbow CP planning approach finds a sufficient number of observation points on the CP needed to observe the TR. The novelty of our rainbow CP planning approach is that it partitions the TR into different shapes with different properties needed to obtain complete coverage while achieving first order path differentiability. The main technical contributions of the proposed approach is to provide a holistic solution that segments any TR, uses triangulation to determine the line of sights and observation points, and computes the collision-free CP within a quadratic runtime. The proposed method can be readily generalized to address problems of higher dimensions, and it is scalable with respect to the size of TR and the number of robots. Computer simulations are used to illustrate the effectiveness and correctness of the proposed approach. [ABSTRACT FROM AUTHOR]

A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays.The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim–Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values. [ABSTRACT FROM PUBLISHER]

A new class of codes, Extended Product (EPC) Codes, consisting of a product code with a number of extra parities added, is presented and applications for erasure decoding are discussed. An upper bound on the minimum distance of EPC codes is given, as well as constructions meeting the bound for some relevant cases. A special case of EPC codes, Extended Integrated Interleaved (EII) codes, which naturally unify Integrated Interleaved (II) codes and product codes, is defined and studied in detail. It is shown that EII codes often improve the minimum distance of II codes with the same rate, and they enhance the decoding algorithm by allowing decoding on columns as well as on rows. It is also shown that EII codes allow for encoding II codes with an uniform distribution of the parity symbols. [ABSTRACT FROM PUBLISHER]

An interior penalty discontinuous Galerkin method for solving 2-D magnetostatic field problems using the magnetic vector potential A is presented. The use of the A -formulation in two dimensions results in a second-order elliptic boundary value problem. Due to the proposed method, the scheme is symmetric and the resulting mass matrix is block diagonal, whereas each block belongs to one element of the triangulation. The applicability of the method is demonstrated by solving a simple 2-D C-shaped ferromagnetic material with a coil surrounding one part of the magnetic yoke. Thereby, the permeability of the material is supposed to be homogeneous and isotropic. The solution A and the resulting field quantities are compared with the standard finite element analysis. [ABSTRACT FROM AUTHOR]

The complete camera pose (location + orientation) of the Google street view (GSV) images is provided by Google. Hence, one can utilize this information to localize a query camera based on the projective geometry. The existing literature works either perform image retrieval-based rough location recognition or require high-computational power/specific features for three-dimensional fine localization. In this paper, we propose a robust 2-D method for outdoor image-based localization using the GSV database. Having found the nearest neighboring images (best matches) in the GSV database using image retrieval techniques or the GPS circle information, the proposed method can be applied for robust fine localization of pedestrians/vehicles. The proposed method first finds the common features among the three views, i.e., query view and two from the best matches. Next, for each common feature, a 2-D triangulation is performed using the retrieved database images to find the feature world coordinates. We call this procedure “2DTri.” Afterward, a novel set of nonlinear equations is solved to estimate the fine location of the query. The novel set of equations can be interpreted as a 2-D version of the well-known perspective n-point (PnP) problem, which we call “2DPnP.” Hence, the proposed method is named “2DTriPnP.” The 2DPnP step is performed in a robust way, which is more accurate and considerably less complex compared to the conventional RANSAC-based robust methods. 2DTriPnP will be demonstrated experimentally to show better localization performance compared to other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Crowd behavior analysis has recently emerged as an increasingly important and dedicated problem for crowd monitoring and management in the visual surveillance community. In particular, it is receiving a lot of attention to detect potentially dangerous situations and to prevent overcrowdedness. In this paper, we propose to quantify crowd properties by a rich set of visual descriptors. The calculation of these descriptors is realized through a novel spatio-temporal model of the crowd. It consists of modeling time-varying dynamics of the crowd using local feature tracks. It also involves a Delaunay triangulation to approximate neighborhood interactions. In total, the crowd is represented as an evolving graph, where the nodes correspond to the tracklets. From this graph, various mid-level representations are extracted to determine the ongoing crowd behaviors. In particular, the effectiveness of the proposed visual descriptors is demonstrated within three applications: crowd video classification, anomaly detection, and violence detection in crowds. The obtained results on videos from different data sets prove the relevance of these visual descriptors to crowd behavior analysis. In addition, by means of comparisons to other existing methods, we demonstrate that the proposed descriptors outperform the state-of-the-art methods with a significant margin using the most challenging data sets. [ABSTRACT FROM PUBLISHER]

Random refraction occurs in turbulence and through a wavy water-air interface. It creates distortion that changes in space, time and with viewpoint. Localizing objects in three dimensions (3D) despite this random distortion is important to some predators and also to submariners avoiding the salient use of periscopes. We take a multiview approach to this task. Refracted distortion statistics induce a probabilistic relation between any pixel location and a line of sight in space. Measurements of an object's random projection from multiple views and times lead to a likelihood function of the object's 3D location. The likelihood leads to estimates of the 3D location and its uncertainty. Furthermore, multiview images acquired simultaneously in a wide stereo baseline have uncorrelated distortions. This helps reduce the acquisition time needed for localization. The method is demonstrated in stereoscopic video sequences, both in a lab and a swimming pool. [ABSTRACT FROM PUBLISHER]

Object triangulation, 3-D object tracking, feature correspondence, and camera calibration are key problems for estimation from camera networks. This paper addresses these problems within a unified Bayesian framework for joint multi-object tracking and camera calibration, based on the finite set statistics methodology. In contrast to the mainstream approaches, an alternative parametrization is investigated for triangulation, called disparity space. The approach for feature correspondence is based on the probability hypothesis density (phd) filter, and hence inherits the ability to handle the initialization of new tracks as well as the discrimination between targets and clutter within a Bayesian paradigm. The phd filtering approach then forms the basis of a camera calibration method from static or moving objects. Results are shown on simulated and real data. [ABSTRACT FROM AUTHOR]

In order to improve the quality of steel pipes, one of the main requisites is to build pipes that are as close as possible to the designed one. To accomplish this task, an optical distance sensor of reduced size and very low power consumption was developed inside a measurement system allowing reconstruction of steel pipe dimensions. The results obtained led to the construction of a working prototype configured as an active triangulation rangefinder with a gamut of 10 cm starting at 5 cm. The characterization of the novel rangefinder has confirmed the feasibility of this new system with a resolution of \sim 10~\mu \textm on a range of measurement of 10 cm, providing up to 10 000 measurements per second. [ABSTRACT FROM PUBLISHER]

Solder ball height and substrate coplanarity inspection is essential to the detection of potential connectivity issues in semi-conductor units. Current ball height and substrate coplanarity inspection tools such as laser profiling, fringe projection, and confocal microscopy are expensive, require complicated setup and are slow, which makes them difficult to use in a real-time manufacturing setting. Therefore, a reliable, in-line ball height and substrate coplanarity measurement method is needed for inspecting units undergoing assembly. [ABSTRACT FROM AUTHOR]

This paper proposes a method for designing base station (BS) clusters and cluster patterns for pair-wise BS coordination. The key idea is that each BS cluster is formed by using the second-order Voronoi region, and the BS clusters are assigned to a specific cluster pattern by using edge-coloring for a graph drawn by Delaunay triangulation. The main advantage of the proposed method is that the BS selection conflict problem is prevented, while users are guaranteed to communicate with their two closest BSs in any irregular BS topology. With the proposed coordination method, analytical expressions for the rate distribution and the ergodic spectral efficiency are derived as a function of relevant system parameters in a fixed irregular network model. In a random network model with a homogeneous Poisson point process, a lower bound on the ergodic spectral efficiency is characterized. Through system level simulations, the performance of the proposed method is compared with that of conventional coordination methods: dynamic clustering and static clustering. Our major finding is that, when users are dense enough in a network, the proposed method provides the same level of coordination benefit with dynamic clustering to edge users. [ABSTRACT FROM AUTHOR]

We developed a new method for extracting 3D flight trajectories of droplets using high-speed stereo capture. We noticed that traditional multi-camera tracking techniques fare poorly on our problem, in part due to the fact that all droplets have very similar shapes, sizes and appearances. Our method uses local motion models to track individual droplets in each frame. 2D tracks are used to learn a global, non-linear motion model, which in turn can be used to estimate the 3D locations of individual droplets even when these are not visible in any camera. We have evaluated the proposed method on both synthetic and real data and our method is able to reconstruct 3D flight trajectories of hundreds of droplets. The proposed technique solves for both the 3D trajectory of a droplet and its motion model concomitantly, and we have found it to be superior to 3D reconstruction via triangulation. Furthermore, the learned global motion model allows us to relax the simultaneity assumptions of stereo camera systems. Our results suggest that, even when full stereo information is available, our unsynchronized reconstruction using the global motion model can significantly improve the 3D estimation accuracy. [ABSTRACT FROM PUBLISHER]

Positioning is a fundamental issue in mobile robot applications. It can be achieved in many ways. Among them, triangulation based on angles measured with the help of beacons is a proven technique. Most of the many triangulation algorithms proposed so far have major limitations. For example, some of them need a particular beacon ordering, have blind spots, or only work within the triangle defined by the three beacons. More reliable methods exist; however, they have an increasing complexity, or they require to handle certain spatial arrangements separately. In this paper, we present a simple and new three object triangulation algorithm, known as ToTal, that natively works in the whole plane and for any beacon ordering. We also provide a comprehensive comparison between many algorithms and show that our algorithm is faster and simpler than comparable algorithms. In addition to its inherent efficiency, our algorithm provides a very useful and unique reliability measure that is assessable anywhere in the plane, which can be used to identify pathological cases, or as a validation gate in Kalman filters. [ABSTRACT FROM PUBLISHER]

Positioning is a fundamental issue in mobile robot applications, and it can be achieved in multiple ways. Among these methods, triangulation based on angle measurements is widely used, robust, accurate, and flexible. This paper presents BeAMS, which is a new active beacon-based angle measurement system used for mobile robot positioning. BeAMS introduces several major innovations. One innovation is the use of a unique unsynchronized channel with on–off keying modulated infrared signals to measure angles and to identify the beacons. We also introduce a new mechanism to measure angles: Our system detects a beacon when it enters and leaves an angular window. We show that the estimator resulting from the center of this angular window provides an unbiased estimate of the beacon angle. A theoretical framework for a thorough performance analysis of BeAMS is provided. We establish the upper bound of the variance and validate this bound through experiments and simulations; the overall error measure of BeAMS is lower than \0.24^\circ for an acquisition rate of 10\,\Hz. In conclusion, BeAMS is a low-power, flexible, and robust solution for angle measurement and a reliable component for robot positioning. [ABSTRACT FROM PUBLISHER]

Node self-localization is a key research topic for wireless sensor networks (WSNs). There are two main algorithms, the triangulation method and the maximum likelihood (ML) estimator, for angle of arrival (AOA) based self-localization. The ML estimator requires a good initialization close to the true location to avoid divergence, while the triangulation method cannot obtain the closed-form solution with high efficiency. In this paper, we develop a set of efficient closed-form AOA based self-localization algorithms using auxiliary variables based methods. First, we formulate the self-localization problem as a linear least squares problem using auxiliary variables. Based on its closed-form solution, a new auxiliary variables based pseudo-linear estimator (AVPLE) is developed. By analyzing its estimation error, we present a bias compensated AVPLE (BCAVPLE) to reduce the estimation error. Then we develop a novel BCAVPLE based weighted instrumental variable (BCAVPLE-WIV) estimator to achieve asymptotically unbiased estimation of locations and orientations of unknown nodes based on prior knowledge of the AOA noise variance. In the case that the AOA noise variance is unknown, a new AVPLE based WIV (AVPLE-WIV) estimator is developed to localize the unknown nodes. Also, we develop an autonomous coordinate rotation (ACR) method to overcome the tangent instability of the proposed algorithms when the orientation of the unknown node is near \pi/2. We also derive the Cramér-Rao lower bound (CRLB) of the ML estimator. Extensive simulations demonstrate that the new algorithms achieve much higher localization accuracy than the triangulation method and avoid local minima and divergence in iterative ML estimators. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a novel interactive projection system (IPS), which enables bare-finger touch interaction on regular planar surfaces (e.g., walls, tables), with only one standard camera and one projector. The challenge of bare-finger touch detection is recovering the touching information just from the 2-D image captured by the camera. In our method, the graphical user interface (GUI) button is projected on the surface and is distorted by the finger when clicking it, and there is a significant positive correlation between the button's distortion and the finger's height to the surface. Therefore, we propose a novel, fast, and robust algorithm, which takes advantage of the button's distortion to detect the touch action. The proposed touch detection algorithm is performed in three stages: 1) region of interest extraction through a homography mapping, by which the computational complexity of the following processing is reduced; 2) the button's distortion detection using a special edge detection algorithm, which greatly reduces the errors due to the influence of the finger's shadows and edges; and 3) touch action judgment by the button's distortion. Several applications (e.g., virtual keyboard, power point viewing), which use the proposed touch detection method based on the buttons, are shown in this paper. An evaluation is performed on the virtual keyboard and the results demonstrate that the proposed approach can detect bare-finger touch in real time with the missed detection rate of 1.00%, false detection rate of 2.08%, and touch detection rate of 96.92% at the typical projected distance. [ABSTRACT FROM AUTHOR]

In this paper, a deterministic sensor deployment method based on wavelet transform (WT) is proposed. It aims to maximize the quality of coverage of a wireless sensor network while deploying a minimum number of sensors on a 3-D surface. For this purpose, a probabilistic sensing model and Bresenham's line of sight algorithm are utilized. The WT is realized by an adaptive thresholding approach for the generation of the initial population. Another novel aspect of the paper is that the method followed utilizes a Cat Swarm Optimization (CSO) algorithm, which mimics the behavior of cats. We have modified the CSO algorithm so that it can be used for sensor deployment problems on 3-D terrains. The performance of the proposed algorithm is compared with the Delaunay Triangulation and Genetic Algorithm based methods. The results reveal that CSO based sensor deployment which utilizes the wavelet transform method is a powerful and successful method for sensor deployment on 3-D terrains. [ABSTRACT FROM PUBLISHER]

A sub-wavelength source tracking system utilizing highly miniaturized antennas in the HF range for applications in GPS-denied environments including indoor and urban scenarios is proposed. A technique that combines a high resolution direction finding and radio triangulation utilizing a compact transmit (Tx) and receive (Rx) antenna system is pursued. Numerical models are used to investigate wave propagation and scattering in complex indoor scenarios as a function of frequency. We choose HF band to minimize attenuation through walls and multipath in indoor environments. In order to achieve a compact system, a low-profile and highly miniaturized antenna (\lambda /300 height and \lambda /100 lateral dimensions at 20 MHz) having omnidirectional, vertically polarized field is designed. At such low frequencies, accurate measurement of the phase difference between the signals at the Rx antennas having very small baseline is challenging. To address this issue, a biomimetic circuit that mimics the hearing mechanism of a fly (Ormia Ochracea) is utilized. With this circuit, very small phase differences are amplified to measurable values. The numerical simulations are used to analyze direction of arrival retrieval and source localization in highly cluttered environments. A compact system prototype is also realized and source tracking in complex indoor scenarios is successfully demonstrated. [ABSTRACT FROM AUTHOR]

The localization method of a magnetic dipole based on the magnetic gradient tensor invariants is the Scalar Triangulation And Ranging method (STAR), which is used to solve the multiple solutions problem for the real-time localization of magnetic dipole by the spatial geometric relationship of the tensor rotation invariants. The method is not involved in the measurement of the magnetic field vector greatly affected by the geomagnetic field. Simultaneously, it is very suitable for underground and underwater exploration such as the exploration of unexploded ordnance. But, it has asphericity errors, which can make the azimuth errors of up to 5^\circ. In addition, it is tightly coupled with the magnetic properties of the target. Thus, we proposed an iterative method to correct the asphericity errors. In this method, beginning with the results of the STAR method, the defective parameters obtained by the sensor structure were used to rapidly correct the localization errors and enhance the properties of real-time localization. The relative errors of the components of bearing vector were reduced by a factor of 7, and they were not influenced by the magnetic properties of the target. [ABSTRACT FROM AUTHOR]

A new exact algorithm is proposed to compute the 3D geometric moments of a homogeneous shape defined by an unstructured triangulation of its surface. This algorithm relies on the analytical integration of the moments on tetrahedra defined by the surface triangles and a central point and on a set of recurrent relationships between the corresponding integrals, and achieves linear running time complexities with respect to the number of triangles in the surface mesh and with respect to the number of moments that are computed. This effectively reduces the complexity for computing moments up to order N from N^6 to N^3 with respect to the fastest previously proposed exact algorithm. [ABSTRACT FROM AUTHOR]

Quality evaluation of rolling processes in the metal industry involves an inspection of the shape of the outgoing products in real time during manufacturing. Shape measurement systems are usually based on 3-D reconstructions of the surface of rolled products. As surface properties are crucial, these systems favor contactless techniques. Using 3-D measurements of the surface of rolled products, several geometric properties can be analyzed. In this paper, we analyze how uncertainty is propagated in a contactless shape measurement system designed and developed by the authors and presented in previous published works. This measurement system is based on active triangulation, and it is able to provide inline width and flatness measurements of long, flat-rolled products in harsh industrial environments. The camera model used to calibrate the vision system is described, and it is used to estimate the uncertainty of the reprojected 3-D points on the scene. The system uses the reprojected 3-D points, and the speed of the product movement in the production line to reconstruct its surface. Thus, the uncertainty of the speed is also estimated. Finally, the propagation of both the uncertainty of the 3-D reprojection, and the uncertainty of the speed into the final width and flatness measurements is analyzed. This paper comprises a detailed uncertainty propagation analysis in 3-D shape measurements computed indirectly through functional relationships. [ABSTRACT FROM AUTHOR]

Escape routing for packages and printed circuit boards (PCBs) has been studied extensively in the past. Network flow is pervasively used to model this problem. However, none of the previous works correctly models the diagonal capacity, which is essential for 45 \circ routing in most packages and PCBs. As a result, existing algorithms may either produce routing solutions that violate the diagonal capacity or fail to output a legal routing even though there exists one. In this paper, we propose a new network flow model that guarantees the correctness when diagonal capacity is taken into consideration. This model leads to the first optimal algorithm for escape routing. We also extend our model to handle missing pins. 45 [ABSTRACT FROM AUTHOR]

We present a simple approach to jointly exploit stripmap and ScanSAR acquisitions to generate differential synthetic aperture radar interferometry (DInSAR) time series. In particular, we extend the capability of the Small BAseline Subset (SBAS) approach to compute deformation time series from a set of stripmap images by filling possible temporal gaps in the available SAR data sequence with ScanSAR acquisitions. The starting point of our approach is the raw data focusing step, which is properly carried out to align the characteristics of the ScanSAR images to those of the stripmap ones. To achieve this task, we exploit stripmap processing codes to focus both SAR data types, the ScanSAR ones being processed on a burst-by-burst basis, accounting also for possible differences of the pulse repetition frequency with respect to that of the stripmap data. The coherent combination of the focused bursts generates phase-preserved ScanSAR images with the same output geometry and pixel spacing as the stripmap ones. This allows a straightforward implementation of the next steps of the SBAS processing chain, including the interferogram generation operation. In this case, we concentrate on a selection of small baseline (SB) stripmap-stripmap multilook interferograms identified through a Delaunay triangulation, which are complemented with a set of hybrid SB stripmap-ScanSAR interferograms. This interferogram selection permits us to develop an effective phase unwrapping algorithm based on a two-step processing strategy. Finally, the whole data set of unwrapped interferograms is inverted through the SBAS technique to retrieve the final deformation time series, including both stripmap and ScanSAR data. The proposed stripmap-ScanSAR SBAS process ing approach is particularly attractive because it is very easy to implement since it requires only limited modifications with respect to the conventional stripmap-based SBAS algorithm. Our approach has been applied to descending and ascending hybrid stripmap-ScanSAR data sets of Envisat/ASAR C-band acquisitions from the Big Island of Hawaii. In spite of not including any common-band azimuthal filtering, which would account for the ScanSAR burst spectral properties at the expense of the algorithm simplicity, the presented results show that we may retrieve DInSAR time series with an accuracy ranging between 5 and 10 mm, consistent with previous C-band data analyses using only stripmap data. [ABSTRACT FROM PUBLISHER]

As 3-D displays become more common, the demand for 3-D-related products is rapidly increased. Three-dimensional image sensors based on the time-of-flight (TOF) technique are one of these products and are applied to many applications. In this paper, a new pixel based on the continuous-wave modulation method was proposed to measure the TOF and was embedded in a test complementary metal–oxide–semiconductor (CMOS) image sensor. Compared with other range imagers, no complex control signals, high operating voltage, or multilevel control voltages are needed in this pixel. The chip, with 92 \times 30 pixels, was fabricated using the Taiwan Semiconductor Manufacturing Company's 0.18-\mu\m CMOS standard process, and a time-switched color measurement was applied to this rangefinder system. A pulse train of red, green, and blue lights is emitted sequentially from a light-emitting diode array. The distance is easily calculated from the phase differences, and the color information is estimated using the difference in reflection coefficients under a different light. The measured distance and color are compared with the actual distance and color-corrected images. A color range image with a distance error of 3.56 cm and an L^\ast a^\ast b color difference of 40.23 can be observed. This rangefinder system provides a new perspective to capturing a colored range image. [ABSTRACT FROM PUBLISHER]

To carry out face transformation, this paper presents new numerical algorithms, which consist of two parts, namely, the harmonic models for changes of face characteristics and the splitting techniques for grayness transition. The main method in this paper is a combination of the finite-volume method (FVM) with Delaunay triangulation to solve the Laplace equations in the harmonic transformation of face images. The advantages of the FVM with Delaunay triangulation are given as follows: 1) easy to formulate the linear algebraic equations; 2) good in retaining the pertinent geometric and physical need; and 3) less central processing unit time needed. Numerical and graphical experiments have been conducted for the face transformation from a female (woman) to a male (man), and vice versa. The computed sequential errors are O(N^-(3/2)), where N^2 is the division number of a pixel into subpixels. These computed errors coincide with the analysis on the splitting–shooting method (SSM) with piecewise constant interpolation in the previous paper of Li and Bai. In computation, the average absolute errors of restored pixel grayness can be smaller than 2 out of 256 grayness levels. The FVM is as simple as the finite-difference method (FDM) and as flexible as the finite-element method (FEM). Hence, the FVM is particularly useful when dealing with large face images with a huge number of pixels in shape distortion. The numerical transformation of face images in this paper can be used not only in pattern recognition but also in resampling, image morphing, and computer animation. [ABSTRACT FROM AUTHOR]

Given the hyperspectral-oriented waveband configuration of multiangular CHRIS/Proba imagery, the scope of its application could widen if the present 18-m resolution would be improved. The multiangular images of CHRIS could be used as input for superresolution (SR) image reconstruction. A critical procedure in SR is an accurate registration of the low-resolution images. Conventional methods based on affine transformation may not be effective given the local geometric distortion in high off-nadir angular images. This paper examines the use of a nonrigid transform to improve the result of a nonuniform interpolation and deconvolution SR method. A scale-invariant feature transform is used to collect control points (CPs). To ensure the quality of CPs, a rigorous screening procedure is designed: 1) an ambiguity test; 2) the m-estimator sample consensus method; and 3) an iterative method using statistical characteristics of the distribution of random errors. A thin-plate spline (TPS) nonrigid transform is then used for the registration. The proposed registration method is examined with a Delaunay triangulation-based nonuniform interpolation and reconstruction SR method. Our results show that the TPS nonrigid transform allows accurate registration of angular images. SR results obtained from simulated LR images are evaluated using three quantitative measures, namely, relative mean-square error, structural similarity, and edge stability. Compared to the SR methods that use an affine transform, our proposed method performs better with all three evaluation measures. With a higher level of spatial detail, SR-enhanced CHRIS images might be more effective than the original data in various applications. [ABSTRACT FROM AUTHOR]

In this correspondence, preamble-based least squares (LS) channel estimation in orthogonal frequency division multiplexing (OFDM) systems of the QAM and offset QAM (OQAM) types is considered. The construction of optimal (in the mean squared error (MSE) sense) preambles is investigated, for sparse (a subset of pilot tones, surrounded by nulls) preambles. The two OFDM systems are compared for the same transmit power, which, for cyclic prefix (CP) based OFDM/QAM, also includes the power spent for CP transmission. OFDM/OQAM, with a sparse preamble consisting of equipowered and equispaced pilots embedded in zeros, turns out to perform at least as well as CP-OFDM. Simulations results are presented that verify the analysis. [ABSTRACT FROM AUTHOR]

In this paper, we propose a segment-based triangulation method for building parallel-perspective stereo mosaics using ray interpolation. The currently available fast parallel ray interpolation for stereo mosaicing uses a uniform or regular triangulation technique that does not take advantage of the spatial information. This works well when the interframe displacement in the video is small. However, for large interframe displacements, hence large motion parallax, we observe visual artifacts in the mosaics when the source triangles in the video frames are warped into destination triangles in the mosaics using affine transformations. Our method uses the edge information present in the scene to ensure that triangles do not cross over from one planar facet to the other. The video frames are segmented, and the edges are obtained from the inner boundaries of different segments. A mesh is designed in each segment or region, over which motion between consecutive video frames is constant. Hence, this method avoids unwanted warping of objects with large motion parallax in the scene and reduces the visual artifacts. The performance of our proposed technique is demonstrated on a series of simple-to-complex video imagery collected by utilizing cameras and airborne sensors. [ABSTRACT FROM AUTHOR]