The object tracking problem is an important research topic in computer vision. For real applications such as vehicle tracking and face tracking, there are many efficient and real-time algorithms. In this study, we wil...
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The object tracking problem is an important research topic in computer vision. For real applications such as vehicle tracking and face tracking, there are many efficient and real-time algorithms. In this study, we will focus on the Lucas-Kanade (LK) algorithm for object tracking. Although this method is time consuming, it is effective in tracking accuracy and environment adaptation. In the standard LK method, the sum of squared errors is used as the cost function, while least trimmed squares is adopted as the cost function in this study. The resulting estimator is robust against outliers caused by noises and occlusions in the tracking process. Simulations are provided to show that the proposed algorithm outperforms the standard LK method in the sense that it is robust against the outliers in the object tracking problems.
A phase retrieval technique for multifrequency scattered field acquisition is presented in this paper. The proposed setup is based on indirect holography schemes so that it combines the desired signal with a known ref...
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A phase retrieval technique for multifrequency scattered field acquisition is presented in this paper. The proposed setup is based on indirect holography schemes so that it combines the desired signal with a known reference signal. The setup is used together with a two-dimensional frequency scanning (FS) antenna and, therefore, the positions of scatterers can be retrieved without the need of moving either the antenna or the objects.
AMO is a simple and efficient optimization algorithm which is inspired by animal migration behavior. However, as most optimization algorithms, it suffers from premature convergence and often falls into local optima. T...
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AMO is a simple and efficient optimization algorithm which is inspired by animal migration behavior. However, as most optimization algorithms, it suffers from premature convergence and often falls into local optima. This paper presents an opposition-based AMO algorithm. It employs opposition-based learning for population initialization and evolution to enlarge the search space, accelerate convergence rate, and improve search ability. A set of well-known benchmark functions is employed for experimental verification, and the results show clearly that opposition-based learning can improve the performance of AMO.
We develop a formal system for describing cyclograms in interval temporal logic. We show that it can be applied for modeling and verification (testing correctness) of cyclogram models (CM). We describe how a rule-base...
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We develop a formal system for describing cyclograms in interval temporal logic. We show that it can be applied for modeling and verification (testing correctness) of cyclogram models (CM). We describe how a rule-based knowledge base of a CM and instruments for constructing algorithms that output discrete controlling influences can be used to improve testing quality.
Based on the fixed point concept in functional analysis, an improvement on the traditional spectral method is proposed for nonlinear oscillation equations with periodic solution. The key idea of this new approach ( na...
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Based on the fixed point concept in functional analysis, an improvement on the traditional spectral method is proposed for nonlinear oscillation equations with periodic solution. The key idea of this new approach ( namely, the spectral fixed point method, SFPM) is to construct a contractive map to replace the nonlinear oscillation equation into a series of linear oscillation equations. Usually the series of linear oscillation equations can be solved relatively easily. Different from other existing numerical methods, such as the well-known Runge-Kutta method, SFPM can directly obtain the Fourier series solution of the nonlinear oscillation without resorting to the Fast Fourier Transform (FFT) algorithm. In the meanwhile, the steepest descent seeking algorithm is proposed in the framework of SFPM to improve the computational efficiency. Finally, some typical cases are investigated by SFPM and the comparison with the Runge-Kutta method shows that the present method is of high accuracy and efficiency.
This paper constructs a general fuzzy assignment problem (GFAP) based on a real-world scenario and proposes a solution procedure. Suppose a project team consists of.. workers and a manager. The.. workers are responsib...
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This paper constructs a general fuzzy assignment problem (GFAP) based on a real-world scenario and proposes a solution procedure. Suppose a project team consists of.. workers and a manager. The.. workers are responsible for performing.. jobs and the manager for restraining the total cost. The corresponding cost for a worker to perform his assigned job is not defined deterministically but as a subnormal fuzzy interval with increasing linear membership function. Job quality is then linearly and positively related to the cost of the job and is taken as the performance of the worker. On the other hand, the performance of the manager is negatively related to the total cost and is defined as a fuzzy interval with a decreasing linear membership function. It is common practice for a company to regard the lowest performance among members as the team performance in order to increase overall team performance. Hence, using the max-min criterion, a mixed nonlinear programming model of the GFAP is constructed. The model can be transformed into a general 0-1 fractional programming problem with max-min objective function. An algorithm that combines simplex and trade-off approaches is proposed to solve the problem. A numerical example and the computational results show that the constructed model and the proposed algorithm are useful and efficient.
This work proposes an improved unscented Kalman filter (UKF)-based simultaneous localization and mapping (SLAM) algorithm based on an adaptive unscented Kalman filter (AUKF) with a noise statistic estimator. The algor...
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This work proposes an improved unscented Kalman filter (UKF)-based simultaneous localization and mapping (SLAM) algorithm based on an adaptive unscented Kalman filter (AUKF) with a noise statistic estimator. The algorithm solves the issue that conventional UKF-SLAM algorithms have declining accuracy, with divergence occurring when the prior noise statistic is unknown and time-varying. The new SLAM algorithm performs an online estimation of the statistical parameters of unknown system noise by introducing a modified Sage-Husa noise statistic estimator. The algorithm also judges whether the filter is divergent and restrains potential filtering divergence using a covariance matching method. This approach reduces state estimation error, effectively improving navigation accuracy of the SLAM system. A line feature extraction is implemented through a Hough transform based on the ranging sonar model. Test results based on unmanned underwater vehicle (UUV) sea trial data indicate that the proposed AUKF-SLAM algorithm is valid and feasible and provides better accuracy than the standard UKF-SLAM system.
Recently the one-counter trace languages and the context-free trace languages have been characterized through restricted types of cooperating distributed systems (CD-systems) of stateless deterministic restarting auto...
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Recently the one-counter trace languages and the context-free trace languages have been characterized through restricted types of cooperating distributed systems (CD-systems) of stateless deterministic restarting automata with window size one (so-called stl-det-R(1)-automata) that work in mode '=1' and that use an external counter or pushdown store to determine the successor components within computations. Here we study the deterministic variants of these CD-systems, comparing the resulting language classes to the classes of languages defined by CD-systems of stl-det-R(1)-automata without such an external device and to some classical language families, among them in particular the classes of rational, one-counter, and context-free trace languages. In addition, we present a large number of (non-)closure properties for our language classes.
Time interleaving is one of the most efficient techniques employed in high-speed sampling systems. However, the frequency response mismatch among different channels will create distortion tones that degrade the system...
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Time interleaving is one of the most efficient techniques employed in high-speed sampling systems. However, the frequency response mismatch among different channels will create distortion tones that degrade the system performance. In this paper, a self-adaptive frequency response mismatch compensation method is presented, where the design of compensation filter is optimized with a self-adapting strategy. This digital postprocessing technique realizes the compensation of frequency response effectively and also the increase of the digital bandwidth of the acquisition system. MATLAB-based simulation and an actual two-channel acquisition system test verify the effectiveness of the algorithm.
The present paper proposes a new method for analytical modelling multiservice networks with implemented traffic overflow mechanisms. The basis for the proposed method is a special two-dimensional convolution algorithm...
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The present paper proposes a new method for analytical modelling multiservice networks with implemented traffic overflow mechanisms. The basis for the proposed method is a special two-dimensional convolution algorithm that enables determination of the occupancy distribution and the blocking probability in network systems in which traffic streams of individual classes can be serviced by both primary and alternative resources. The algorithm worked out by the authors makes it possible to model systems with any type of traffic offered to primary resources. In order to estimate the accuracy of the proposed method, the analytical results of blocking probabilities in selected networks with traffic overflow have been compared with simulation data.
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