• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.165-168
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• 2004

This paper propose a target tracker using phase correlation. The tracker consist of a pre-processing module, a translation estimation module based on phase correlation, a fine motion estimation module applied when confidence rate could not fulfill a threshold value and a reference image update module. The fine motion estimation module measure the shift, rotation and scale of input image compared to reference using Fourier-Mellin transform. Proposed tracker was tested its accuracy and robustness using some real indoor and outdoor image sequences.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.64-70
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• 2017

In the commercial building such as huge enterprise building, more accurate operation of the center-controlled roller blind. We design, in this work, the target disc that its shape is nonlinearly changing and the sensor coils that are differentially arranged. The performance shows less than 1% accuracy when it is implemented in the roller blind.

• Progress in Medical Physics
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• v.20 no.4
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• pp.324-330
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• 2009

In this study, we evaluated accuracy and usefulness of CyberKnife Respiratory Tracking System ($Synchrony^{TM}$, Accuray, USA) about a moving during stereotactic radiosurgery. For this study, we used moving phantom that can move the target. We also used Respiratory Tracking System called Synchrony of the Cyberknife in order to track the moving target. For treatment planning of the moving target, we obtained an image using 4D-CT. To measure dose distribution and point dose at the moving target, ion chamber (0.62 cc) and gafchromic EBT film were used. We compared dose distribution (80% isodose line of prescription dose) of static target to that of moving target in order to evaluate the accuracy of Respiratory Tracking System. We also measured the point dose at the target. The mean difference of synchronization for TLS (target localization system) and Synchrony were $11.5{\pm}3.09\;mm$ for desynchronization and $0.14{\pm}0.08\;mm$ for synchronization. The mean difference between static target plan and moving target plan using 4D CT images was $0.18{\pm}0.06\;mm$. And, the accuracy of Respiratory Tracking System was less 1 mm. Estimation of usefulness in Respiratory Tracking System was $17.39{\pm}0.14\;mm$ for inactivity and $1.37{\pm}0.11\;mm$ for activity. The mean difference of absolute dose was $0.68{\pm}0.38%$ in static target and $1.31{\pm}0.81%$ in moving target. As a conclusion, when we treat about the moving target, we consider that it is important to use 4D-CT and the Respiratory Tracking System. In this study, we confirmed the accuracy and usefulness of Respiratory Tracking System in the Cyberknife.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.445-450
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• 2015

In the moving target problem, the velocity information of the moving target is very important as well as the high accuracy position information. To solve this problem, active researches are being conducted recently with combine the Time Difference of Arrival (TDOA) and Frequency Delay of Arrival(FDOA) measurements. However, since the FDOA measurement is utilizing the Doppler effect due to the relative velocity between the target source and the receiver sensor, it may be difficult to use the FDOA measurement if the moving target speed is not sufficiently fast. In this paper, we propose a method for estimating the position and the velocities of the target by using only the TDOA measurements for the low speed moving target in the indoor environment with sensor network. First, the target position and heading angle are obtained from the estimated positions of two attached transmitters on the target. Then, the target angular and linear velocities are also estimated. In addtion, we apply the Instrumental Variable (IV) technique to compensate the estimation error of the estimated target velocity. In simulation, the performance of the proposed algorithm is verified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.382-387
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• 1992

In order to obtain desired arc welding performance, we already developed an arc welding robot system that enabled coordinated motions of dual arm robots. In this system one robot arm holds a welding target as a positioning device, and the other robot moves the welding torch. Concerning to such a dual arm robot system, the positioning accuracy of robots is one important problem, since nowadays conventional industrial robots unfortunately don't have enough absolute accuracy in position. In order to cope with this problem, our robot system employed teaching playback method, where absolute error are compensated by the operator's visual feedback. Due to this system, an ideal arc welding considering the posture of the welding target and the directions of the gravity has become possible. Another problem still remains, while we developed an original teaching method of the dual arm robots with coordinated motions. The problem is that manual teaching tasks are still tedious since they need fine movements with intensive attentions. Therefore, we developed a 3-dimensional vision guided robot control method for our welding robot system with coordinated motions. In this paper we show our 3-dimensional vision sensor to guide our arc welding robot system with coordinated motions. A sensing device is compactly designed and is mounted on the tip of the arc welding robot. The sensor detects the 3-dimensional shape of groove on the target work which needs to be weld. And the welding robot is controlled to trace the grooves with accuracy. The principle of the 3-dimensional measurement is depend on the slit-ray projection method. In order to realize a slit-ray projection method, two laser slit-ray projectors and one CCD TV camera are compactly mounted. Tactful image processing enabled 3-dimensional data processing without suffering from disturbance lights. The 3-dimensional information of the target groove is combined with the rough teaching data they are given by the operator in advance. Therefore, the teaching tasks are simplified

• Korean Journal of Applied Biomechanics
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• v.34 no.1
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• pp.34-44
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• 2024

Objective: This study aimed to investigate how the movements occurring during the follow-through phase after releasing an arrow among elite compound archers, are associated with the arrow impact points on the target. Method: Nine elite archers performed consecutive compound archery shooting under conditions identical to actual competitions using their own bows and equipment. Motion capture system and force platform were utilized to record the changes in joint positions and center of pressure, respectively. Principal component analysis was employed to identify the patterns in which multidimensional joint positions and COP changes were organized with horizontal and vertical coordinates of arrow impact points. Subsequently, correlation analysis quantified the relationship between individual variables and the coordinates of arrow impacts on the target. Results: We found a common organizational pattern in which the two axes of the impact point coordinates were grouped into the first two principal components. The movements of the upper and lower limbs following release exhibited opposite patterns in the anterior-posterior axis, with significant correlations observed between the arrow impact points of the horizontal axis and the left shoulder, right elbow, left hip, and both knees. Additionally, the lateral movements induced by the reaction force upon arrow release showed significant associations with the vertical coordinates of the impact points. Particularly, the correlations between the movements of the left shoulder and elbow, as well as the bilateral hip and right knee, were consistently observed among all participants. Conclusion: These findings implied that the post-release movements could significantly influence the trajectory and impact points of the arrows in compound archery. We suggest that a consistent and controlled movement during the follow-through phase may be more beneficial for optimizing shooting accuracy and precision rather than minimizing movements.

• Aerospace Engineering and Technology
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• v.6 no.1
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• pp.237-244
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• 2007

Estimation of target position is one of the main functions of surveillance UAVs, and is being used to various purposes but generally noisy target position is estimated due to the existence of random measurement errors. In this report, a method of diminishing target position estimation error by calculating target position using Kalman Filtered optimum values such as position, attitude of UAV and sight vector of optical instrument, is proposed.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.65-71
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• 2016

To reduce the expenses for development a novel drug, systems biology has been studied actively. Target prediction, a part of systems biology, contributes to finding a new purpose for FDA(Food and Drug Administration) approved drugs and development novel drugs. In this paper, we propose a classification model for predicting novel target genes based on relation between target genes and disease related genes. After collecting known target genes from TTD(Therapeutic Target Database) and disease related genes from OMIM(Online Mendelian Inheritance in Man), we analyzed the effect of target genes on disease related genes based on PPI(Protein-Protein Interactions) network. We focused on the distinguishing characteristics between known target genes and random target genes, and used the characteristics as features for building a classifier. Because our model is constructed using information about only a disease and its known targets, the model can be applied to unusual diseases without similar drugs and diseases, while existing models for finding new drug-disease associations are based on drug-drug similarity and disease-disease similarity. We validated accuracy of the model using LOOCV of ten times and the AUCs were 0.74 on Alzheimer's disease and 0.71 on Breast cancer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1066-1079
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• 2023

Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.