• ALGAE
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• 제34권4호
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• pp.315-326
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• 2019

Northeastward drifts of massive Sargassum patches were observed in the East China Sea (ECS) and Yellow Sea (YS) by the Geostationary Ocean Color Imager (GOCI) in May 2017. Coverage of the brown macroalgae patches was the largest ever recorded in the ECS and YS. Three-dimensional circulation modeling and Lagrangian particle tracking simulations were conducted to reproduce drifting trajectories of the macroalgae patches. The trajectories of the macroalgae patches were controlled by winds as well as surface currents. A windage (leeway) factor of 1% was chosen based on sensitivity simulations. Southerly winds in May 2017 contributed to farther northward intrusion of the brown macroalgae into the YS. Although satellite observation and numerical modeling have their own limitations and associated uncertainties, the two methods can be combined to find the best estimate of Sargassum patch trajectories. When satellites were unable to capture all patches because of clouds and sea fog in the ECS and YS, the Lagrangian particle tracking model helped to track and restore the missing patches in satellite images. This study suggests that satellite monitoring and numerical modeling are complementary to ensure accurate tracking of macroalgae patches in the ECS and YS.

• Journal of Power Electronics
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• 제18권5호
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• pp.1470-1478
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• 2018

Recently, wireless power transfer (WPT) via coupled magnetic resonances has attracted a lot of attention owing to its long operation distance and high efficiency. However, the WPT systems is over-coupling and a frequency splitting phenomenon occurs when resonators are placed closely, which leads to a decrease in the transfer power. To solve this problem, an adaptive frequency tracking control (AFTC) was used based on a closed-loop control scheme. An improved particle swarm optimization (PSO) algorithm was proposed with the AFTC to track the maximum power point in real time. In addition, simulations were carried out. Finally, a WPT system with the AFTC was demonstrated to experimentally validate the improved PSO algorithm and its tracking performance in terms of optimal frequency.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.467-473
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• 2007

In this paper, we present a position-based robot hand tracking scheme where a pan-tilt camera is controlled such that a robot hand is always shown in the center of an image frame. We calculate the rotation angles of a pan-tilt camera by transforming the coordinate systems. In order to identify the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. From the simulation results, it is shown that the considered parameter identification problem is characterized by a highly multimodal landscape; thus, a global optimization technique such as a particle swarm optimization could be a promising tool to identify the model parameters of a robot hand tracking system, whereas the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum.

• International Journal of Contents
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• 제10권3호
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• pp.17-25
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• 2014

In this paper, we describe an adaptive Markov chain Monte Carlo-based particle filter that effectively addresses real-time multi-face tracking on mobile platforms. Because traditional approaches based on a particle filter require an enormous number of particles, the processing time is high. This is a serious issue, especially on low performance devices such as mobile phones. To resolve this problem, we developed a tracker that includes a more sophisticated likelihood model to reduce the number of particles and maintain the identity of the tracked faces. In our proposed tracker, the number of particles is adjusted during the sampling process using an adaptive sampling scheme. The adaptive sampling scheme is designed based on the average acceptance ratio of sampled particles of each face. Moreover, a likelihood model based on color information is combined with corner features to improve the accuracy of the sample measurement. The proposed tracker applied on various videos confirmed a significant decrease in processing time compared to traditional approaches.

• 로봇학회논문지
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• 제5권3호
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• pp.262-269
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• 2010

This paper presents a probabilistic head tracking method, mainly applicable to face recognition and human robot interaction, which can robustly track human head against various variations such as pose/scale change, illumination change, and background clutters. Compared to conventional particle filter based approaches, the proposed method can effectively track a human head by regularizing the sample space and sequentially weighting multiple visual cues, in the prediction and observation stages, respectively. Experimental results show the robustness of the proposed method, and it is worthy to be mentioned that some proposed probabilistic framework could be easily applied to other object tracking problems.

• 한국산업융합학회 논문집
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• 제27권2_2호
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• pp.319-324
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• 2024

In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.

• 한국통신학회논문지
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• 제37권5A호
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• pp.375-387
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• 2012

본 연구에서는 움직이는 CCD 카메라로부터 입력된 영상에서 색상 및 질감 성분을 기반으로 하는 파티클 필터를 이용하여 실시간으로 객체를 추적할 수 있는 알고리즘을 제안한다. 초기 영상에서 추적하고자 하는 객체를 선택하면 이를 타깃 파티클로 결정하고, 타깃 파티클로 부터 추적을 위한 초기 상태가 모델링 된다. 이후 프레임부터 N개의 파티클들이 랜덤 분포로 생성되고 각 파티클로 부터 질감 정보인 로컬 CS-LBP (Centre Symmetric Local Binary Patterns)모델과 색상 분포 모델이 특징 모델로 사용된다. 각 특징 모델에 대해 바타차리야 (Bhattacharyya) 거리를 사용하여 각 파티클과 타깃 파티클 간의 특징 관측 우도(likelihood)를 구하고 이를 각 파티클의 가중치로 설정 한다. 각 파티클의 가중치를 기반으로 가중치가 가장 높은 파티클을 새로운 타깃으로 설정하고, 각 파티클들을 재 샘플링 한다. 본 실험결과에서는 여러 가지 특징을 조합하여 실험을 하였고, 그 결과 색상 분포 모델과 로컬 CS-LBP를 조합했을 때 추적 성능이 가장 우수한 것을 확인할 수 있었다.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2001년도 추계학술대회 논문집
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• pp.213-219
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• 2001

In this paper, particle velocity of slurry flow, a kind of solid-particle two phase flow, was measured by using a particle tracking velocimetry. Particles are modeled by sphere-shaped glass whose diameters are 3mm, 5mm, and 7mm At first, a particle which is falling in the water is captured and analyzed to give their free falling velocity. The falling velocity was very high up to about 4m/sec in the air, which needs special algorithm for the accurate measurement. For the upwelling slurry flow in the straight duct, there are some noises caused by cavity. However, the effect was so small that it does not affect the measurement of large particles. From the preliminary study of applying the PTV to measurement of particle movement in slurry flow, we could find out the optimum value of parameters: threshold value., searching area radius and correlation area size.

• 한국정보통신학회논문지
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• 제11권3호
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• pp.584-591
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• 2007

연속되는 이미지 중에서 인간의 동작을 인식하는 것은 인간과 컴퓨터의 상호 작용에서 매우 중요하고 도전할 분야이다. 본 논문에서는 CONDENSATION 알고리즘을 이용하여 입자 필터(particle filter)에 기반한 동작 인식 알고리즘을 제안한다. 입자 필터는 조건 확률 전파 모델(Conditional Density Propagation)인 베이시안(Bayesian) 추정 규칙을 적용하는 추적구조를 갖고 있기 때문에 일반적으로 기존 추적 알고리즘보다 뛰어난 성능을 갖는 경향이 있다. 본 논문에서는 알고리즘의 성능 평가를 위해서 두 개의 동작 모델을 가정하였고, 영상에 대한 전처리를 위해서는 MATLAB를 이용하였으며 입자필터는 고속 처리를 위하여 C++로 구현하였다. 두 개의 동작 실험 결과를 통해, 동작 인식 입자 필터가 근접한 동작 환경 속에서 강인한 추적 성능을 나타냄을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 C
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• pp.1210-1212
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• 1997

This study describes the influence of the size of the median particles of alumina trihydrated(ATH) filler on the tracking resistance, tensile properties, dielectric properties and water immersion properties of EPDM rubber. A fixed 100pph concentration of the filler of A TH was used for all particle sizes from 0.7 to $20{\mu}m$. It is shown that tracking and erosion resistance decrease with increasing particle size, whereas tensile properties and dielectric properties are improved with increasing particle size of ATH.