• Journal of the Ergonomics Society of Korea
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• v.16 no.3
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• pp.1-10
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• 1997

This paper is concerned with the development and evaluation of the camera calibration method for a real-time head tracking system. Tracking of head movements is important in the design of an eye-controlled human/computer interface and the area of virtual environment. We proposed a video-based head tracking system. A camera was mounted on the subject's head and it took the front view containing eight 3-dimensional reference points(passive retr0-reflecting markers) fixed at the known position(computer monitor). The reference points were captured by image processing board. These points were used to calculate the position (3-dimensional) and orientation of the camera. A suitable camera calibration method for providing accurate extrinsic camera parameters was proposed. The method has three steps. In the first step, the image center was calibrated using the method of varying focal length. In the second step, the focal length and the scale factor were calibrated from the Direct Linear Transformation (DLT) matrix obtained from the known position and orientation of the camera. In the third step, the position and orientation of the camera was calculated from the DLT matrix, using the calibrated intrinsic camera parameters. Experimental results showed that the average error of camera positions (3- dimensional) is about $0.53^{\circ}C$, the angular errors of camera orientations are less than $0.55^{\circ}C$and the data aquisition rate is about 10Hz. The results of this study can be applied to the tracking of head movements related to the eye-controlled human/computer interface and the virtual environment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.2
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• pp.9-18
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• 2014

This paper proposes the fuzzy PI controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, this paper proposes the MPPT control using the fuzzy PI controller that can be improve a MPPT control performance. The fuzzy PI controller is adjusted a input of PI controller by fuzzy control and compensated a cumulative error of fuzzy control by PI controller. The fuzzy PI MPPT control is compared to conventional PO and IC MPPT method for various temperature and radiation condition. This paper proves the validity of the fuzzy PI controller using these results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1864-1871
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• 2012

This paper proposes the hybrid proportional integral(HBPI) controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation and influence of a shadow. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, in order to solve these problems, this paper proposes HBPI controller that is adjusted gain of conventional PI control using fuzzy control, and the maximum power point tracks using this controller. The validity of the controller proposed in this paper proves through the results of the comparisons.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.210-212
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• 2009

In object tracking based on the particle filter algorithm controlling the proper distribution of the samples is essential to accurately track the target. If the samples are spread too wide compared to the target size, the tracking accuracy may degrade as some samples can be caught by background clutters that is similar to the target. On the other hands if the samples are spread too narrow, the particle filter may fail to track the abrupt motion of the target. To solve this problem we propose an improved particle filter that adopts "re-weighting" technique at the observe step. We estimate the distribution of the weights of the current samples by its mean and variance. Then the samples are re-weighted so that the appropriate distribution of the samples in proportional to the target scale is obtained at the next select step. The proposed tracking method can avoid convergence to local mean and improve the accuracy of the estimated target state.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.447-448
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• 2006

In this paper, we propose tracking algorithm using multi resolution in wavelet transform domain. This algorithm consists of two steps. The first step is feature extraction that is select feature-points using 1-level wavelet transform in ROI (Region of Interest). The other step is feature tracking. Based on multi resolution of wavelet transform, we estimate a displacement between current frame and next frame on the basis of selected feature-points. Experimental results show that the proposed algorithm confirmed a better performance than a centroid tracking and correlation tracking.

• ETRI Journal
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• v.37 no.3
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• pp.551-561
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• 2015

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2358-2361
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• 2001

In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks which have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, this paper first has a global search of entire image and tracks the object through local search when the object is recognized.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.5
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• pp.1115-1121
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• 2001

This paper presents the development of a tracking algorithm for shipborad satellite antenna systems which can enhance the tracking performance. In order to overcome some drawbacks of the conventional step tracking algorithm a new tracking algorithm is proposed. The proposed algorithm searches for the best tracking angles using gradient-based formulae and signal intensities measured according to a search pattern. The effectiveness of the proposed algorithm is demonstrated through simulation using real data.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1411-1414
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• 2003

In this paper, vehicle tracking is implemented using parametric active contour. Extract objects from the background area is the essential step in vehicle tracking. We focus our algorithm on the situations such that the camera is fixed. However, if a simple and ordinary algorithm is adapted to achieve real-time processing, it produces much noise and the vehicle tracking results is poor. For this reason, in this paper, we propose a parametric active contour model algorithm to achieve better vehicle tracking. Experimental results show that the performance of the proposed algorithm is satisfactory.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.219-224
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• 2001

This paper presents the development of a tracking algorithm for shipboard satellite antenna systems which can enhance the tracking performance. In order to overcome some drawbacks of the conventional step tracking algorithm, the proposed algorithm searches for the best tracking angles using gradient-based formulae and signal intensities measured according to a search pattern. The effectiveness of the proposed algorithm is demonstrated through simulation using real-world data.