• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1307-1317
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• 2018

To deal with the problems of occlusion, pose variations and illumination changes in the object tracking system, a regression model weighted multi-templates mean-shift (MS) algorithm is proposed in this paper. Target templates and occlusion templates are extracted to compose a multi-templates set. Then, the MS algorithm is applied to the multi-templates set for obtaining the candidate areas. Moreover, a regression model is trained to estimate the Bhattacharyya coefficients between the templates and candidate areas. Finally, the geometric center of the tracked areas is considered as the object's position. The proposed algorithm is evaluated on several classical videos. The experimental results show that the regression model weighted multi-templates MS algorithm can track an object accurately in terms of occlusion, illumination changes and pose variations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.295-298
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• 1995

We performed a research to improve the performance of active bar model which is used in tracking algorithm. Active bar model is a simplified model of snake model. If we used the sctive bar model, the numerical procedure for real time tracking problem can be carried out faster than snake model. However the demerit of active bar algorithms is that we can't used the provious image data because each time it has to reconstruct the active bar. In this paper we proposed advanced algorithm for active bar model. The proposed model can improve tracking abilities by preserving the active bar during the process and changing the energy functional.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.35-53
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• 2007

We consider a(worst-case) robust optimization version of the Economic Order Quantity(EOQ) model. Order setup costs and inventory carrying costs are assumed to have uncertainty in their values, and the uncertainty description of the two parameters is supposed to be given by an ellipsoidal representation. A genetic algorithm combined with Monte Carlo simulation is proposed to approximate the ellipsoidal representation. The objective function of the model under ellipsoidal uncertainty description is derived, and the resulting problem is solved by another genetic algorithm. Computational test results are presented to show the performance of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.836-842
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• 2015

In this paper, the target size and model based target size estimator (TMBE) algorithm is presented for iimaging infrared (IIR) seeker. At the imaging seeker, target size information is important factor for accurate tracking. The model based target size estimator filter (MBEF) algorithm was proposed to estimate target size at imaging infrared seeker. But, the model based target size estimator filter algorithm need to know relative distance from the target. In order to overcome the problem, we propose target size and model based target size estimator filter (TMBEF) algorithm which based on the target size. The performance of proposed algorithm is tested at target intercept scenario. The experiment results show that the proposed algorithm has the accurate target size estimating performance.

• Proceedings of the KOR-KST Conference
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• 2002.02a
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• pp.97-139
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• 2002

The aim of the present study is to find a good quality user equilibrium assignments under time varying condition. For this purpose, this study introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it develops a novel solution algorithm that does not need evaluation of the objective function by modifying the Schittenhelm (1990)'s algorithm. This novel algorithm turns out to be efficient and convenient compared to the conventional Frank-Wolfe (1956) algorithm because the former finds solutions based on routes rather than links so that it can maintain correct flow propagation intrinsically in the time-varying network conditions. The application of dynamic user equilibrium (DUE) assignment model with this novel solution algorithm to test networks including medium-sized one shows that the present DUE assignment model gives rise to high quality discrete time solutions when we adopt the deterministic queuing model for a link performance function, and we associate flows and costs in a proper way.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.115-125
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• 2004

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problems are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed-model production lines, the two problems have been considered separately. A genetic algorithm for balancing and sequencing in mixed-model U line is proposed. A presentation method and genetic operators are proposed. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that the proposed algorithm is promising in solution quality.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1004-1011
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• 2016

The inaccurate model parameters in the predictive current control of surface-mounted permanent magnet synchronous motor (SMPMSM) affect the current dynamic response and steady-state error. This paper presents a model parameter correction algorithm based on the relationship between the errors of model parameters and the static errors of dq-axis current. In this correction algorithm, the errors of inductance and flux are corrected in two steps. Resistance is ignored. First, the proportional relations between inductance and d-axis static current errors are utilized to correct the error of model inductance. Second, the flux is corrected by utilizing the proportional relations between flux and q-axis static current errors under the condition that inductance is corrected. An experimental study with a 100 W SMPMSM is performed to validate the proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.11-19
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• 1994

The matching probability P(ο/$\lambda$), of the signal sequence(ο) observed for a finite time interval with a HMM (Hidden Markov Model $\lambda$) indicates the probability that signal comes from the given model. By utilizing the fact that the probability represents matching score of the observed signal with the model we can recognize an unknown signal pattern by comparing the magnitudes of the matching probabilities with respect to the known models. Because the algorithm however uses floating point variables during the computing process hardware implementation of the algorithm requires floating point units. This paper proposes an integer algorithm which uses positive integer numbers rather than float point ones to compute the matching probability so that we can economically realize the algorithm into hardware. The algorithm makes the model parameters integer numbers by multiplying positive constants and prevents from divergence of data through the normalization of variables at each step. The final equation of matching probability is composed of constant terms and a variable term which contains logarithm operations. A scheme to make the log conversion table smaller is also presented. To analyze the qualitive characteristics of the proposed algorithm we attatch simulation result performed on two groups of 10 hypothetic models respectively and inspect the statistical properties with repect to the model order the magnitude of scaling constants and the effect of the observation length.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.5
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• pp.51-58
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• 2004

In this paper, a mesh simplification algorithm is proposed which considers the conservation of the volume of a 3D model. In General, most of mesh simplification algorithm use a distance metric. The distance metric is very efficient to measure geometric error, but it causes volume changes between the original model and the simplified model. In this paper a mesh simplification algorithm which conserves the volume of the original model is suggested. A new vertex resulting from an edge contraction, takes a position which conserves the volume of the 3D model using the proposed algorithm. Although the new algorithm needs more time than the QEM algorithm, it is shown that it conserves the original volumn of the 3D model during the simplification.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.177-180
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• 2000

An algorithm for modeling of yeast fermentation process using genetic-fuzzy algorithm is presented in this work. The algorithm involves developing the fuzzy modeling of the process and model update capability against the system change. The membership functions of state variables and specific rates and the decision table were generated using genetic algorithm. This algorithm could replace the complex mathematical model to simple fuzzy model and cope with the change of process characteristics well.