• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.640-647
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• 2018

This study analyzes the tracking accuracy(tracking errors) of fighter radar. Measurement error, detection failure, and radar cross section(RCS) fluctuation in radar measurements degrade the measurement quality and hence affect the tracking accuracy. Therefore, these radar measurement characteristics need to be considered when analyzing the tracking accuracy. In this paper, a method for analyzing the tracking accuracy is proposed; this method considers the detection error, detection probability, and RCS fluctuation. Results from experiments conducted with the proposed method show that the detection probability and RCS fluctuation affect tracking accuracy.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.367-373
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• 2016

In this paper, we propose a novel method to improve the accuracy of eye trackers and how to analyze them. The proposed method extracts a user profile information created by extracting gaze coordinates and color information based on the exact pupil information, and then, it maintains a high accuracy in the display. In case that extract the user profile information, the changes of the accuracy for the gaze time also is estimated and the optimum parameter value is extracted. In the experimental results for the accuracy of the gaze detection, the accuracy was low if a user took a short time in a specific point. On the other hand, when taking more than two seconds, the accuracy was measured more than 80 %.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.9
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• pp.828-836
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• 2015

In this paper, the assessment technique for track accuracy in the phased array radar is proposed. It is assumed that ${\alpha}-{\beta}$ tracking filter to track the target is established in the phased array radar. In order to assess the track accuracy strictly, we should use the real target position data acquired from the special instrument, ACMI(Air Combat Maneuvering Instrument) pod or DGPS(Differential Global Positioning System). However, this method leads to increase the experiment cost and test time. We derive the relationship between the residuals of tracking filter and the standard deviations of range and angle tracking errors which are assigned as track assessment index. The theory of sample variance is introduced in this assessment because track accuracy has to be calculated with many residual samples.

• Annual Conference of KIPS
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• 2009.11a
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• pp.399-400
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• 2009

무마커 기반 증강현실 응용에서 빠르고 정확한 무마커 추적이 수행되어야 한다. 무마커 추적은 등록된 패턴의 특징점들과 입력 영상에서의 특징점들의 매칭을 통하여 수행된다. 매칭에서 이상점은 시차를 크게 유발시키는 요인이 되므로 정확도 향상을 위해서는 이상점을 제거해야 한다. 본 논문에서는 무마커 추적의 정확도 향상을 위한 이상점 제거 방식을 제안한다. 무마커 추적에서 사용되는 SURF 알고리즘을 사용하여 실영상을 캡처하여 실험하였고 정확도 및 실행시간을 비교하였다.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.139-146
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• 2007

Many researches had been gone about method to track moving object using wireless sensor network. We examined tradeoffs that exist between quantity of energy and correctness of tracking, and we confirmed that can get more energy sayings through improved motion prediction method. The consumed energy in the tracking is used by sensor node for sensing the object, and tracking correctness is a differ once of actual object position from calculated value by sensing. Some tracking methods and controlling parameters causes a variation of tracking correctness and energy consuming, we can get best energy effectiveness by motion prediction algorithm. Furthermore, we get better tracking quality and energy effectiveness through using a motion prediction algorithm that consider acceleration. By the simulation, we know that if we use an accurate motion prediction algorithm, node activation range that is used for target's predicted position should be restricted to sensing range of sensor is better.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.610-615
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• 2015

The accuracy and precision of video-based remote gaze trackers is affected by numerous factors (e.g. the head movement of the participant). However, it is challenging to control all factors that have an influence, and doing so (e.g., using a chin-rest to control geometry) could lead to losing the benefit of using gaze trackers, i.e., the ecological validity of their unobtrusive nature. We propose an adaptive zoom-based gaze tracking technique, ZoomTrack that addresses this problem by improving the resolution of the gaze tracking results. Our approach magnifies a region-of-interest (ROI) and retrieves gaze points at a higher resolution under two different zooming modes: only when the gaze reaches the ROI (temporary) or whenever a participant stares at the stimuli (omnipresent). We compared these against the base case without magnification in a user study. The results are then used to summarize the advantages and limitations of our technique.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.257-263
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• 1997

원자력 발전소의 주급수 유량은 원자로 열출력 산출에 사용되는 중요한 변수로서 , 노심관리 뿐만 아니라 원자로 안전 운전에도 중요하며, 발전소 출력에 직접적인 영향을 미친다. 원자력발전소의 주급수 유량은 1% 의 허용오차로 설계되어 있으나, 사용년수의 증가 및 운전조건의 영향 둥으로 정확도의 유지가 어려운 실정이다. 주급수 유량을 정확도 $\pm$0.5% 이내로 측정한다면 1000 MW 급 원자력 발전소에서 최대 10MW 의 전기출력 복구가 가능하며, 이를 위해 주급수 유량 측정 설비의 정확도 검증과 보정을 할 수 있는 정확한 유량 측정법의 개발이 절실하다. 본 연구에서는 화학 추적자 방법에 의한 정밀 유량 측정기술을 개발하여, 원자력 발전소 주급수 계통의 유량 측정에 사용되고 있는 벤츄리(venturi), 노즐(nozzle), 오리피스(orifice) 등의 유량검증에 활용함으로서 발전소의 안전성을 유지하면서 동시에 출력을 극대화하는 것을 목표로 하여 추적자 이용 유량 검증기를 설계 제작하였으며 그 정확도와 유효성에 대한 실험적 검토를 하였다. 본 연구에서 사용한 추적자 방법은 유량 번동에 좋은 응답성을 보이고 있으며, 유량 측정에 있어서도 정확도 $\pm$ 0.5 % 이내의 매우 신뢰성 있는 측정이 가능하다.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.77-83
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• 2019

In this paper, we propose an object tracking algorithm based on color histogram and convolutional neural network model. In order to increase the tracking accuracy, we synthesize generic object tracking using regression network algorithm which is one of the convolutional neural network model-based tracking algorithms and a mean-shift tracking algorithm which is a color histogram-based algorithm. Both algorithms are classified through support vector machine and designed to select an algorithm with higher tracking accuracy. The mean-shift tracking algorithm tends to move the bounding box to a large range when the object tracking fails, thus we improve the accuracy by limiting the movement distance of the bounding box. Also, we improve the performance by initializing the tracking start positions of the two algorithms based on the average brightness and the histogram similarity. As a result, the overall accuracy of the proposed algorithm is 1.6% better than the existing generic object tracking using regression network algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.63-73
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• 2021

The radar operated to detect/track aircraft targets is divided into a search radar that operates while the antenna rotating device rotates for the purpose of detecting the target according to the mission characteristics, and a tracking radar that periodically steers and tracks a beam to the predicted position of the target. The tracking radar has a shorter target information acquisition preiod than the search radar. Due to this characteristic, the tracking accuracy is better than that of the search radar, but as the prediction error increases due to the speed error at the beginning of the tracking, there are many cases in which tracking fails at the beginning of tracking due to failure to perform beam steering normally. In this paper, in order to solve the above-mentioned problems, we propose an algorithm for improving the accuracy of track initiation using radial velocity measurements in addition to the position of the measured, and confirm the performance of the proposed algorithm by comparing with the two point differential algorithm

• Annual Conference of KIPS
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• 2013.05a
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• pp.374-376
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• 2013

증강 현실(Argument Reality)에 대한 관심이 증가함에 따라 빠르고 강건한 물체 추적(Object Tracking)기법의 개발이 큰 이슈가 되고 있다. 특히, 마커를 사용하지 않는 경우에 추적 속도와 정확도의 정보가 이루어지는 강건한 Markerless 3D 추적 기술은 많은 연구가 이루어지고 있다. 본 논문에서는 SIFT(Scale Invariant Feature Transform)를 이용한 특징점 추출 및 매칭 기법을 통하여 높은 정확도의 물체 추적기법을 제안한다. 그리고 실시간으로 적용하기 어려운 SIFT의 느린 특징점 추출과 매칭 단계를 GPU 기반의 병렬화 작업을 통하여 개선시켜 향상된 추적 속도를 보여준다.