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Thermal infrared (TIR) object tracking is one of the most challenging tasks in computer vision. This paper proposes a robust TIR tracker based on the continuous correlation filters and adaptive feature fusion (RCCF-TIR). Firstly, the Efficient Convolution Operators (ECO) framework is selected to build the new tracker. Secondly, an optimized feature set for TIR tracking is adopted in the framework. Finally, a new strategy of feature fusion based on average peak-to-correlation energy (APCE) is employed. Experiments on the VOT-TIR2016 (Visual Object Tracking-TIR2016) and PTB-TIR (A Thermal Infrared Pedestrian Tracking Benchmark) dataset are carried out and the results indicate that the proposed RCCF-TIR tracker combines good accuracy and robustness, performs better than the state-of-the-art trackers and has the ability to handle various challenges.

In this paper, we studied a diffusive predator-prey model with competitive interference and Crowley-Martin type functional response. The conditions for local stability of coexisting equilibrium are given by analyzing the eigenvalue spectrum. By using delay as bifurcation parameter, conditions for occurrence of Hopf bifurcation are also given. The property of bifurcating period solutions is investigated by calculating the normal form. Some numerical simulations are performed to support our theoretical result. Our conclusions show that diffusion and delay are two factors that should be considered in establishing the predator-prey model, since they can induce spatially bifurcating period solutions.

Three-dimensional (3D) digital images are helpful in studying the physical properties of a medium. Moreover, reconstructing a 3D image from a two-dimensional (2D) image via computer-mathematical modeling is an important process. Based on the relationship between cascaded grids, an ingenious cascaded polymorphic method is proposed in this work to reconstruct a 3D image from a 2D image. By using the cascaded polymorphic method, a patch can be copied directly into a reconstruction grid by matching the patterns between cascaded grids; the polymorphism of the templates correspond to the grid size. To improve the reconstruction performance further, the non-edge region expansion strategy for a layer and the non-edge region replication strategy for adjacent layers were also proposed. A core sample and building material were selected as the test materials, and several effective measurements were used as quantitative means. To display the reconstruction effect intuitively, 2D reconstruction experiments were also performed along with the 3D experiment. The results show that the reconstruction speed is significantly improved using the cascaded polymorphic method, and the morphological features of the 3D reconstruction are clearly promoted.

To achieve higher detection rate and lower false alarm rate in dim and small target detection, this paper proposes a novel approach based on the Local Region Similarity Difference (LRSD). Then the regions where the true targets and suspected target areas exist in are extracted. To further eliminate the false target regions, we process the LRSD image with pipeline filter and then the true target is finally obtained. Experimental results on some real-life infrared (IR) images with different types of targets verify that the proposed method could effectively prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, experimental results demonstrate its superior and reliable detection performance by high detection rate and low false alarm rate.

In this paper, estimation of parameters in the extended growth curve model without assumption of normality is presented via outer product least squares for covariance (COPLS). The COPLS estimator for covariance can be explicitly expressed and proved to follow a linear transformation of k + 1 independent Wishart distributions for a normal error matrix, where k is the number of profiles of the growth curve. Then two-stage generalized least squares (GLS) estimators for regression coefficients are elaborately derived. Finally, the COPLS estimator and the two-stage GLS estimators are shown to have desired properties both in finite and large samples. Simulation studies for finite sample sizes are provided to confirm that the COPLS estimator and the two-stage GLS estimators are alternative competitors with some evident merits to the existing maximum likelihood estimators in small samples. A real data set is analyzed to demonstrate the proposed methodology.

This paper considers the estimating problem of a panel data partially linear model with spatial autoregressive errors and fixed effects. In addition, we allow the idiosyncratic errors to be intertemporally correlated. By combining the polynomial spline series approximation, the semiparametric least squares method and the difference based technique, a new generalized moment estimator for the autoregressive parameter of the spatial model is constructed. Its consistency and asymptotic normality are established. In order to avoid the incidental parameter problem, a difference based intertemporal covariance matrix estimator is proposed. Based on the estimated spatially and time-wise correlated error structure, we further construct a weighted difference based semiparametric least squares estimator (WDSLSE) and a weighted difference based polynomial spline series estimator (WDPSSE) for the parametric and nonparametric components of the mean model, respectively. We develop an asymptotic theory for these two estimators, including the asymptotic normality, asymptotic efficiency and convergence rate. In particular, we show that the parametric component estimator has the same asymptotic distribution as that based on completely known spatial autoregressive parameter and intertemporal covariance matrix. Simulation studies demonstrate that our asymptotic theory is applicable for finite samples, and the analysis of a real data set illustrates the usefulness of our developed methodology.

Roll-pitch gimballed infrared seeker has wide field of view but suffers from the rapid roll motion of the zenith-pass problem. For estimating the line-of-sight (LOS) rate with the roll-pitch seeker, we propose a coordinate transformation method to compensate for the impact of rapid roll motion. A precise LOS rate dynamics model is derived on the transformed coordinate system. And based on the model, we design a novel LOS rate estimator with the Improved Iterated Cubature Kalman Filter algorithm (IICKF). The proposed IICKF is derived from reducing the dimensionality of the optimization problem of the ICKF, which inherits the estimation accuracy but decreases the computational complexity of the algorithm. For validating, Monte Carlo simulations are performed at last. The simulation results show that the proposed LOS rate estimator outperform the standard EKF, CKF, ICKF, and can well cope with the rapid roll motion of the zenith-pass problem in roll-pitch gimballed infrared seeker system.

In this paper, we propose a framework of outer product least squares for covariance (COPLS) to directly estimate covariance in the growth curve model based on an analogy, between the outer product of a data vector and covariance of a random vector, and the ordinary least squares technique. The COPLS estimator of covariance has an explicit expression and is shown to have the following properties: (1) following a linear transformation of two independent Wishart distribution for a normal error matrix; (2) having asymptotic normality for a nonnormal error matrix; and (3) having unbiasedness and invariance under a linear transformation group. And, a corresponding two-stage generalized least squares (GLS) estimator for the regression coefficient matrix in the model is obtained and its asymptotic normality is investigated. Simulation studies confirm that the COPLS estimator and the two-stage GLS estimator of the regression coefficient matrix are satisfying competitors with some evident merits to the existing maximum likelihood estimator in finite samples.

This paper investigates estimation of parameters in a combination of the multivariate linear model and growth curve model, called a generalized GMANOVA model. Making analogy between the outer product of data vectors and covariance yields an approach to directly do least squares to covariance. An outer product least squares estimator of covariance (COPLS estimator) is obtained and its distribution is presented if a normal assumption is imposed on the error matrix. Based on the COPLS estimator, two-stage generalized least squares estimators of the regression coefficients are derived. In addition, asymptotic normalities of these estimators are investigated. Simulation studies have shown that the COPLS estimator and two-stage GLS estimators are alternative competitors with more efficiency in the sense of sample mean, standard deviations and mean of the variance estimates to the existing ML estimator in finite samples. An example of application is also illustrated.

Objective A direct-current, cold atmospheric-pressure air plasma microjet (PMJ) was performed to inactivate Staphylococcus aureus (S. aureus) and Enterococcus faecalis (E. faecalis) in air. The process of sterilization and morphology of bacteria was observed. We wish to know the possible inactivation mechanisms of PMJ and explore a potential application in dental and other temperature sensitive treatment. Methods In this study, we employed a direct current, atmospheric pressure, cold air PMJ to inactivate bacterias. Scanning electron microscopy was employed to evaluate the morphology of S. aureus and showed rupture of cell walls after the plasma treatment and Optical emission spectrum (OES) were used to understand the possible inactivation mechanisms of PMJ. Results The inactivation rates could reach 100% in 5 min. When the distance between the exit nozzle of the PMJ device and Petri dish was extended from 1 cm to 3 cm, effective inactivation was also observed with a similar inactivation curve. Conclusion The inactivation of bacteria is attributed to the abundant reactive oxygen and nitrogen species, as well as ultroviolet radiation in the plasma. Different life spans and defensibilities of these killing agents may hold the key to understanding the different inactivation curves at different treatment distances.

The failure rate of the mixture of two normal distributions in an unequal variance case may have four changes in monotonicity. This work analyzes the conditions for which the four changes occur and others for which increasing failure rate and modified bathtub shape can be shown.