• Journal of Welding and Joining
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• v.14 no.5
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• pp.113-121
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• 1996

The arc sensor has been most widely used for weld seam tracking through welding current or voltage variation. In this work, the relation between the arc light intensity and welding condition is investigated using heat balance in the Plasma for its possible application to seam tracking in the GMAW process. The arc light intensity is derived to be the function of the arc length and welding current Experiments are carried out to verify the proposed heat balance model. Performances of least square and integration methods to process the signals for seam tracking are compared experimentally. Predicted arc light intensity shows reasonably good agreement with experimental results. The weld seam is successfully tracked through the arc light intensity. The least square and integration methods demonstrate almost same performance of seam tracking with $CO_2$gas shielding.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.775-778
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• 1996

In this research, the robustness of a seam tracking for the automatic welding system is studied. The laser displacement sensor is used as a seam finder. X-Y moving table drived by ac servo motor controls the position and velocity of the torch-and-sensor part. However, dc servo motor is used to control the position and velocity of the torch. The sensor locates ahead of torch to preview the weld line, and brings about the inaccuracy on the torch tracking. To enhance the robustness on this system against the influence of disturbances and model uncertainty, H$\_$.inf./ control is applied to the angular motion of torch. The simulation shows that the tracking accuracy improved significantly. Also, experimental results give a good performance of H$\_$.inf./ control strategy to the automatic seam tracking system for the welding.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.579-582
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• 2015

The Mean-Shift is a robustness algorithm that can be used for tracking the object using the similarity of histogram distributions of target model and target candidate. However, Mean-shift using hue information has disadvantage of tracking a wrong target when the target and background has similar hue distributions. We then propose a robust Mean-Shift tracking algorithm using new image that combined upper 4bit-planes in hue and saturation, respectively.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.2
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• pp.47-54
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• 1992

In this paper, a new extended JPDA (Joint Probabilistic Data Association) tracking algorithm which has more excellent performance than that of the conventional JPDA algorithm in case of the tracking of crossing targets is proposed. In the proposed extended JPDA algorithm, the velocity parameters as well as the position parameters are included to compute the association probabilities between tracks and measurement data. Then the tracking performance of crossing targets is improved and the track bias of parallel moving targets can be reduced. Accordingly, in this paper, the new extended JPDA algorithm for multitarget tracking is proposed and its good performance is shown through the computer simulation. And, tracking performance of extended JPDA algorithm is also compared with that of JPDA algorithm with our noise model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2217-2229
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• 2015

Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.211-211
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• 2000

The multiple targets tracking problem has been one of main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimension filter, input estimation filter, interacting multiple model (IMM) filter, federated variable dimension filter with input estimation, probable data association (PDA) filter etc. have been proposed to address the tracking and sensor fusion issues. In this paper, two existing tracking algorithms, i.e. the IMMPDA filter and the variable dimension filter with input estimation (VDIE), are combined for the purpose of improving the tracking performance of maneuvering targets in clutter. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns i.e. Waver, Pop-Up, and High-Diver motions, are defined and are applied to the modified IMMPDA filter considered as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMMPDA filter than the standard IMM filter are demonstrated through computer simulations.

• Journal of Ocean Engineering and Technology
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• v.23 no.2
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• pp.47-52
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• 2009

A Lagrangian particle tracking model coupled with the Princeton Ocean Model were used to estimate the average residence time of coastal water in Masan Bay, Korea. Our interest in quantifying the transport time scales in Masan Bay was stimulated by the search for a mechanistic understanding of this spatial variability, which is consistent with the concept of spatially variable transport time scales. Tidal simulation was calibrated through a comparison with the results of semi-diurnal current and water elevation measured at the tidal stations of Masan, Gadeokdo. In the model simulations, particles were released in eight cases, including slack before ebb, peak ebb, slack before flood, and peak flood, during both spring and neap tides. The averaged values obtained from the particle release simulations were used for the average residence times of the coastal water in Masan Bay. The average residence times for the southeastern parts of Somodo and the Samho River, Masan Bay were estimated to be about 20~50days and 70~80days, respectively. The spatial difference for the average residence time was controlled by the tidal currents and distance from the mouth of the bay. Our results might provide useful for understanding the transport and behavior of coastal water in a bay and might be used to estimate the dissimilative capacity for environmental assessment.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.25-32
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• 2016

In this paper, we propose a method that is tracking an object in real time using particle filter and the observation model with edge. First of all, the proposed method defines the object to be tracked in the initial frame. Then, it generates the edge observation model for the object to be tracked and a set of particles. It calculates the weight by comparing the average of the middle distance in eight-way of particle filter edge model with that in edge observation model, and then updates the weight with the calculated value. After resampling particles using the updated weights, it estimates the current location of the tracked object. Finally, this paper demonstrates the performance of the stable tracking through comparison with the existing method by using a number of experimental data.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.1
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• pp.1-9
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• 2016

In this paper, we integrate three degree of freedom(3DOF) point-mass model for aircraft and three-dimensional path generation algorithms using dubins curve and nonlinear path tracking law. Through this integration, we apply the path generation algorithm to the path planning, and verify tracking performance and feasibility of using the aircraft 3DOF point-mass model for air traffic management. The accuracy of modeling 6DOF aircraft is more accurate than that of 3DOF model, but the complexity of the calculation would be raised, in turn the rate of computation is more likely to be slow due to the increase of degree of freedom. These obstacles make the 6DOF model difficult to be applied to simulation requiring real-time path planning. Therefore, the 3DOF point-mass model is also sufficient for simulation, and real-time path planning is possible because complexity can be reduced, compared to those of the 6DOF. Dubins curve used for generating the optimal path has advantage of being directly available to apply path planning. However, we use the algorithm which extends 2D path to 3D path since dubins curve handles the two dimensional path problems. Control law for the path tracking uses the nonlinear path tracking laws. Then we present these concomitant simulation results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.204-207
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• 2009

This paper presents how to implement Markerless Augmented Reality and how to create and apply reference data sets. There are three parts related with implementation: setting camera, creation of reference data set, and tracking. To create effective reference data sets, we need a 3D model such as CAD model. It is also required to create reference data sets from various viewpoints. We extract the feature points from the model image and then extract 3D positions corresponding to the feature points using ray tracking. These 2D/3D correspondence point sets constitute a reference data set of the model. Reference data sets are constructed for various viewpoints of the model. Fast tracking can be done using a reference data set the most frequently matched with feature points of the present frame and model data near the reference data set.