Global motion estimation with Gabor wavelet transform

A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform （GWT）, a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decision approach proposed. Then, the initialized motion vectors are obtained via a hierarcbal block-matching based on these checkpoints. Finally, by employing a 3-parameter motion model, precise parameters of global motion are found. From the experiment, the algorithm is reliable and robust.

Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data

Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide（a.k.a algal bloom） model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.

Electronic image stabilization system based on global feature tracking

A new robust electronic image stabilization system is presented, which involves feature-point, tracking based global motion estimation and Kalman filtering based motion compensation. First, global motion is estimated from the local motions of selected feature points. Considering the local moving objects or the inevitable mismatch, the matching validation, based on the stable relative distance between the points set is proposed, thus maintaining high accuracy and robustness. Next, the global motion parameters are accumulated for correction by Kalman filteration. The experimental result illustrates that the proposed system is effective to stabilize translational, rotational, and zooming jitter and robust to local motions.

EXISTENCE OF GLOBAL SMOOTH SOLUTIONS FOR TWO IMPORTANT NONSTRICTLY QUASILINEAR HYPERBOLIC SYSTEMS

In this paper,we study the global smooth solutions of the Cauchy problem for two important nonstrictly quasilinear hyperbolic systems.i.e.,the isentropic gas dynamics system in Euler coordinates (Ⅰ) and the rotational degeneracy of hyperbolic systems of conservation laws(Ⅱ).sufficient conditions which guarantee the existence of gloats smooth solutions of the Cauchy problems (Ⅰ) and (Ⅱ) are obtained by employing the characteristic method.

Distributed bearing-based formation control of unmanned aerial vehicle swarm via global orientation estimation

Most existing formation control approaches for Unmanned Aerial Vehicle(UAV)swarm assume that global position and global coordinate frame are directly available for each agent.To extend the application domain,this paper proposes a distributed bearing-based formation control scheme,without any reliance on global position or global coordinate frame.The interactions among UAVs are described by a directed topology with two-leader structure.To address the issue of unavailable global coordinate frame,we first present a distributed orientation estimation law for each UAV to determine its orientation under the coordinate frame of the first leader.Based on the orientation estimation,we then design a bearing-based formation control law to globally asymptotically track target moving formations.Finally,simulation results are provided to validate the proposed method,which show that the translation,scale and orientation of the formation can be flexibly controlled via two leaders.

Using Event-Based Method to Estimate Cybersecurity Equilibrium

Estimating the global state of a networked system is an important problem in many application domains.The classical approach to tackling this problem is the periodic(observation)method,which is inefficient because it often observes states at a very high frequency.This inefficiency has motivated the idea of event-based method,which leverages the evolution dynamics in question and makes observations only when some rules are triggered(i.e.,only when certain conditions hold).This paper initiates the investigation of using the event-based method to estimate the equilibrium in the new application domain of cybersecurity,where equilibrium is an important metric that has no closed-form solutions.More specifically,the paper presents an event-based method for estimating cybersecurity equilibrium in the preventive and reactive cyber defense dynamics,which has been proven globally convergent.The presented study proves that the estimated equilibrium from our trigger rule i)indeed converges to the equilibrium of the dynamics and ii)is Zeno-free,which assures the usefulness of the event-based method.Numerical examples show that the event-based method can reduce 98%of the observation cost incurred by the periodic method.In order to use the event-based method in practice,this paper investigates how to bridge the gap between i)the continuous state in the dynamics model,which is dubbed probability-state because it measures the probability that a node is in the secure or compromised state,and ii)the discrete state that is often encountered in practice,dubbed sample-state because it is sampled from some nodes.This bridge may be of independent value because probability-state models have been widely used to approximate exponentially-many discrete state systems.

A Two-Stage Algorithm of High Resolution Image Alignment for Mobile Applications

Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.

A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19

Objective:Coronavirus disease 2019(COVID-19)exists as a pandemic.Mortality during hospitalization is multifactorial,and there is urgent need for a risk stratification model to predict in-hospital death among COVID-19 patients.Here we aimed to construct a risk score system for early identification of COVID-19 patients at high probability of dying during in-hospital treatment.Methods:In this retrospective analysis,a total of 821 confirmed COVID-19 patients from 3 centers were assigned to developmental(n=411,between January 14,2020 and February 11,2020)and validation(n=410,between February 14,2020 and March 13,2020)groups.Based on demographic,symptomatic,and laboratory variables,a new Coronavirus estimation global(CORE-G)score for prediction of in-hospital death was established from the developmental group,and its performance was then evaluated in the validation group.Results:The CORE-G score consisted of 18 variables(5 demographics,2 symptoms,and 11 laboratory measurements)with a sum of 69.5 points.Goodness-of-fit tests indicated that the model performed well in the developmental group(H=3.210,P=0.880),and it was well validated in the validation group(H=6.948,P=0.542).The areas under the receiver operating characteristic curves were 0.955 in the developmental group(sensitivity,94.1%;specificity,83.4%)and 0.937 in the validation group(sensitivity,87.2%;specificity,84.2%).The mortality rate was not significantly different between the developmental(n=85,20.7%)and validation(n=94,22.9%,P=0.608)groups.Conclusions:The CORE-G score provides an estimate of the risk of in-hospital death.This is the first step toward the clinical use of the CORE-G score for predicting outcome in COVID-19 patients.

Phase Residual Estimations for PCVs of Spaceborne GPS Receiver Antenna and Their Impacts on Precise Orbit Determination of GRACE Satellites

In-flight phase center systematic errors of global positioning system（GPS） receiver antenna are the main restriction for improving the precision of precise orbit determination using dual-frequency GPS.Residual approach is one of the valid methods for in-flight calibration of GPS receiver antenna phase center variations（PCVs） from ground calibration.In this paper,followed by the correction model of spaceborne GPS receiver antenna phase center,ionosphere-free PCVs can be directly estimated by ionosphere-free carrier phase post-fit residuals of reduced dynamic orbit determination.By the data processing of gravity recovery and climate experiment（GRACE） satellites,the following conclusions are drawn.Firstly,the distributions of ionosphere-free carrier phase post-fit residuals from different periods have the similar systematic characteristics.Secondly,simulations show that the influence of phase residual estimations for ionosphere-free PCVs on orbit determination can reach the centimeter level.Finally,it is shown by in-flight data processing that phase residual estimations of current period could not only be used for the calibration for GPS receiver antenna phase center of foretime and current period,but also be used for the forecast of ionosphere-free PCVs in future period,and the accuracy of orbit determination can be well improved.

Global Gradient Estimate on Graph and Its Applications

Continuing our previous work （arXiv：1509.07981vl）, we derive another global gradient estimate for positive functions, particularly for positive solutions to the heat equation on finite or locally finite graphs. In general, the gradient estimate in the present paper is independent of our previous one. As applications, it can be used to get an upper bound and a lower bound of the heat kernel on locally finite graphs. These global gradient estimates can be compared with the Li-Yau inequality on graphs contributed by Bauer et al. [J. Differential Geom., 99, 359-409 （2015）]. In many topics, such as eigenvalue estimate and heat kernel estimate （not including the Liouville type theorems）, replacing the Li-Yau inequality by the global gradient estimate, we can get similar results.

RRVPE:A Robust and Real-Time Visual-Inertial-GNSS Pose Estimator for Aerial Robot Navigation

Self-localization and orientation estimation are the essential capabilities for mobile robot navigation.In this article,a robust and real-time visual-inertial-GNSS(Global Navigation Satellite System)tightly coupled pose estimation(RRVPE)method for aerial robot navigation is presented.The aerial robot carries a front-facing stereo camera for self-localization and an RGB-D camera to generate 3D voxel map.Ulteriorly,a GNSS receiver is used to continuously provide pseudorange,Doppler frequency shift and universal time coordinated(UTC)pulse signals to the pose estimator.The proposed system leverages the Kanade Lucas algorithm to track Shi-Tomasi features in each video frame,and the local factor graph solution process is bounded in a circumscribed container,which can immensely abandon the computational complexity in nonlinear optimization procedure.The proposed robot pose estimator can achieve camera-rate(30 Hz)performance on the aerial robot companion computer.We thoroughly experimented the RRVPE system in both simulated and practical circumstances,and the results demonstrate dramatic advantages over the state-of-the-art robot pose estimators.

Construction of Solutions and L^1-error Estimates of Viscous Methods for Scalar Conservation Laws with Boundary

This paper is concerned with an initial boundary value problem for strictly convex conservation laws whose weak entropy solution is in the piecewise smooth solution class consisting of finitely many discontinuities. By the structure of the weak entropy solution of the corresponding initial value problem and the boundary entropy condition developed by Bardos-Leroux Nedelec, we give a construction method to the weak entropy solution of the initial boundary value problem. Compared with the initial value problem, the weak entropy solution of the initial boundary value problem includes the following new interaction type： an expansion wave collides with the boundary and the boundary reflects a new shock wave which is tangent to the boundary. According to the structure and some global estimates of the weak entropy solution, we derive the global L^1-error estimate for viscous methods to this initial boundary value problem by using the matching travelling wave solutions method. If the inviscid solution includes the interaction that an expansion wave collides with the boundary and the boundary reflects a new shock wave which is tangent to the boundary, or the inviscid solution includes some shock wave which is tangent to the boundary, then the error of the viscosity solution to the inviscid solution is bounded by O（ε^1/2） in L^1-norm; otherwise, as in the initial value problem, the L^1-error bound is O（ε｜ In ε｜）.

Symmetric jump processes and their heat kernel estimates

We survey the recent development of the DeGiorgi-Nash-Moser-Aronson type theory for a class of symmetric jump processes(or equivalently,a class of symmetric integro-differential operators).We focus on the sharp two-sided estimates for the transition density functions(or heat kernels) of the processes,a priori Hlder estimate and parabolic Harnack inequalities for their parabolic functions.In contrast to the second order elliptic differential operator case,the methods to establish these properties for symmetric integro-differential operators are mainly probabilistic.

An Efficient Class of Calibration Ratio Estimators of Domain Mean in Survey Sampling

This paper develops a new approach to domain estimation and proposes a new class of ratio estimators that is more efficient than the regression estimator and not depending on any optimality condition using the principle of calibration weightings.Some wellknown regression and ratio-type estimators are obtained and shown to be special members of the newclass of estimators.Results of analytical study showed that the new class of estimators is superior in both efficiency and biasedness to all related existing estimators under review.The relative performances of the new class of estimators with a corresponding global estimator were evaluated through a simulation study.Analysis and evaluation are presented.

ORDER RESULTS OF GENERAL LINEAR METHODS FOR MULTIPLY STIFF SINGULAR PERTURBATION PROBLEMS

Presents a study that analyzed the erroneous behavior of general linear methods applied to some classes of one-parameter multiply stiff singularly perturbed problems. Numerical representation of the problem; Computation of the global error estimate of algebraically and diagonally stable general linear methods; Implications of the results for the case of Runge-Kutta methods.