• The Journal of the Acoustical Society of Korea
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• v.24 no.1E
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• pp.34-37
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• 2005

Ryu et al. proposed a multiple target angle-tracking algorithm without a data association problem using angular innovations. This algorithm, however, needs the computational loads in proportion to the square number of sensors regardless of the number of targets, because it uses a nonlinear equation between the signal subspace and angular innovation. In this Paper, we proposed an efficient algorithm for the multiple target angle-tracking using angular innovations. The proposed algorithm extracts the angular innovations from noise subspace. Also, it is demonstrated by computer simulations dealing with the tracking of crossing targets. The simulation results show that the computational loads of the proposed algorithm are $80\%$ and $60\%$ of those of Ryu's algorithm for 3 targets and 6 targets without degrading the performance of the target tracking.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.6
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• pp.433-441
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• 2020

This study proposes a constant power tracking algorithm to compensate for the intermittent characteristics of Photovoltaic connected to a DC micro grid. A PV-ESS integrated module in which distributed ESS is additionally connected is utilized for the proposed algorithm. PV performs P&O MPPT control at all times. To supplement the intermittent characteristics of PV, the proposed constant power tracking algorithm maintains constant power by operating the distributed ESS of the PV-ESS integrated module in accordance with the output state of the PV. By performing PSIM simulation and an experiment, this study verifies the performance of the integrated module of PV-ESS for DC micro grids applying the constant power tracking algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.536-542
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• 2016

To enhance tracking efficiency, a target-tracking filter with a resource management algorithm is required. One of the resource management algorithms chooses or evaluates the proper sampling time using cost functions which are related to the target tracking filter. We propose a resource management algorithm for bearing only tracking environments. Since the tracking performance depends on the system observability, the bearing-only tracking is one of challenging target-tracking fields. The proposed algorithm provides the adaptive sampling time using the variation rate of the error covariance matrix from the target-tracking filter. The simulation verifies the efficiency performance of the proposed algorithm.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.14-23
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. However, in this paper, multipass tracking more than single pass tracking is performed by conventional seam tracking algorithm and developed one. And tracking performances of two algorithm are compared in multipass tracking. As the result, tracking performance in multi-pass welding shows superior conventional seam tracking algorithm to developed one.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.3
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• pp.133-141
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• 2002

Most maximum power point tracking(MPPT) control algorithm is based on Perturb and Observe(P&O) and Incremental Conductance(IncCond). In comparison with P&O and IncCond algorithm, the dynamic and tracking characteristic of IncCond algorithm is better than P&O algorithm in condition of rapidly changing solar radiation. But in the case of digital implementation, the InCond algorithm has error en decision of maximum power operation point(MPOP). To solve this problem, this paper proposes a improved IncCond algorithm, which can determine the MPOP correctly by inserting the test signal in control input. This paper proposes a novel MPPT control algorithm for the digitally implemented photovoltaic system in condition of rapidly changing solar radiation. To verify the validity of the proposed control algorithm. the computer simulation and experiment are carried out.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.123-130
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• 2004

In this paper, an advanced error tracking algorithm by using feedback channel was proposed for error resilient transmission. Using this proposed algorithm, the propagation of errors were reduced within the decoded data over bit error prone network. The addresses of corrupted blocks are reported to encoder by decoder. With negative acknowledgments of feedback channel, the encoder can precisely calculate negative acknowledgments and track the propagated errors by examining the backward motion dependency for proper pixel in the current encoding frame. The error-propagation effects can be terminated completely by INTRA refreshing the affected macro-blocks by using proposed error tracking algorithm. By utilizing the selective four-corner error tracking approximation, the error tracking computations of the proposed algorithm is less than that of the algorithm using full pixel without substantial degradation in video quality. The proposed algorithm can track errors rapidly and accurately.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.746-751
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• 2006

In this paper, we present tracking algorithm for the indoor moving object. We research passive method using a camera and image processing. It had been researched to use dynamic based estimators, such as Kalman Filter, Extended Kalman Filter and Particle Filter for tracking moving object. These algorithm have a good performance on real-time tracking, but they have a limit. If the shape of object is changed or object is located on complex background, they will fail to track them. This problem will need the complicated image processing algorithm. Finally, a large algorithm is made from integration of dynamic based estimator and image processing algorithm. For eliminating this inefficiency problem, image based estimator, Mean-shift Algorithm is suggested. This algorithm is implemented by color histogram. In other words, it decide coordinate of object's center from using probability density of histogram in image. Although shape is changed, this is not disturbed by complex background and can track object. This paper shows the results in real camera system, and decides 3D coordinate using the data from mean-shift algorithm and relationship of real frame and camera frame.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1415-1429
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• 2019

Nowadays object tracking process becoming one of the most challenging task in Computer Vision filed. A CSR-DCF (channel spatial reliability-discriminative correlation filter) tracking algorithm have been proposed on recent tracking benchmark that could achieve stat-of-the-art performance where channel spatial reliability concepts to DCF tracking and provide a novel learning algorithm for its efficient and seamless integration in the filter update and the tracking process with only two simple standard features, HoGs and Color names. However, there are some cases where this method cannot track properly, like overlapping, occlusions, motion blur, changing appearance, environmental variations and so on. To overcome that kind of complications a new modified version of CSR-DCF algorithm has been proposed by integrating deep learning based object detection and CSRT tracker which implemented in OpenCV library. As an object detection model, according to the comparable result of object detection methods and by reason of high efficiency and celerity of Faster RCNN (Region-based Convolutional Neural Network) has been used, and combined with CSRT tracker, which demonstrated outstanding real-time detection and tracking performance. The results indicate that the trained object detection model integration with tracking algorithm gives better outcomes rather than using tracking algorithm or filter itself.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.112-118
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• 2014

This paper deals with a color-based tracking of a moving object. Firstly, existing Camshift algorithm is complemented to improve the tracking weakness in the brightness change of an image which occurs in every frame. The complemented Camshift still shows unstable tracking when the objects with same color of the tracking object exist in background. In order to overcome the drawback this paper proposes the Camshift combined with KLT algorithm based on optical flow. The KLT algorithm performing the pixel-based feature tracking can complement the shortcoming of Camshift. Experimental results show that the merged tracking method makes up for the drawback of the Camshit algorithm and also improves tracking performance.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.187-193
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• 1998

This paper proposes an advanced visual tracking algorithm for the stable grasping of a moving target(2D). This algorithm is programmed to find grasping points of an unknown polygonal object and execute visual tracking. The Kalman Filter(KF) algorithm based on the SVD(Singular Value Decomposition) is applied to the visual tracking system for the tracking of a moving object. The KF based on the SVD improves the accuracy of the tracking and the robustness in the estimation of state variables and noise statistics. In addition, it does not have the numerical unstability problem that can occur in the visual tracking system based on Kalman filter. In the grasping system, a parameterized family is constructcd, and through the family, the grasping system finds the stable grasping points of an unknown object through the geometric properties of the parameterized family. In the previous studies, many researchers have been studied on only 'How to track a moving target'. This paper concern not only on 'how to track' but also 'how to grasp' and apply the grasping theory to a visual tracking system.