• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1741-1748
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• 1995

A new particle tracking algorithm using the concept of match probability between two consequent image frames has been developed to obtain an instantaneous 2-dimensional velocity field. A computer simulation has been carried out to check the performance and usefulness of the developed algorithm by comparing with the conventional 4-frame Particle Tracking Velocimetry(PTV) method. As a result the newly developed algorithm shows very good performance. Although the major part of the developed algorithm is time-consuming iterative updating routine of match probability, computational elapse time to get the resonable results is a very short compared with the 4-frame PTv.Additionally, the present 2-frame PTV algorithm recovers more velocity vectors and has higher dynamic range and lower error ratio compared with the conventional 4-frame PTV.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.143-148
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• 2014

Particle filter algorithm has been proven very successful for non-linear and non-Gaussian estimation problem and thus it has been widely used for object tracking for video signals. If the object moves significantly, particle filter needs very large number of particles to track object and this results high computational cost. In this paper, modified particle filter by adopting motion vector is proposed for tracking vehicle in low frame rate(LPR) video input, which the object moving significantly and randomly between consecutive frames. In the proposed algorithm, motion vector is applied in selection and observe step. The experimental result shows that the proposed particle filter can track vehicle successfully in the case when previous one fails. And it also shows the propose method increases the precision of tracking.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.3
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• pp.443-449
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• 2000

The performance of 2-frame PTV(particle tracking velocimetry) system was improved using an adaptive hybrid scheme. The original 2-frame PTV method based on the match probability concept employs global match parameters for the entire flow field. Since this does not reflect fully the detailed local velocity change, it sometimes reduces the recovery rate of velocity vectors and increases the number of erroneous vectors in the region where an extraordinary flow structure exists. In this study, the preliminary FFT-based PIV results are used as an input parameter to determine the local match parameters needed for the 2-frame particle tracking algorithm. A computer simulation using synthetic particle images was carried out to study the performance of the adaptive 2-frame PTV technique. The adaptive hybrid method shows the better performance with increasing the velocity vector recovery rate and decreasing the computation time, compared to the original 2-frame PTV method.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.3
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• pp.34-42
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• 1994

The present study is aimed to improve the PIV performance by suggesting a two-frame particle identification technique and by introducing estimation method of wall pressure distribution from the velocity data. Adopted image processing system consists of one commercial image board slit into a personal computer, 2-D sheet light generator, flow picture recording apparatus and related particle identification software. A revised particle tracking method essential to PIV performance is obtained by particle centroid correlation pairing (CCP) and its effectiveness is ascertained by comparison with multi-frame identification.

• Journal of Mechanical Science and Technology
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• v.15 no.1
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• pp.108-116
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• 2001

The in-cylinder flow field of gasoline engine comprises unsteady compressible turbulent flows caused by the intake port, combustion chamber geometry. Thus, the quantitative analysis of the in-cylinder flow characteristics plays an important role in the improvement of engine performances and the reduction of exhaust emission. In order to obtain the quantitative analysis of the in-cylinder gas flows for a gasoline engine, the single-frame particle tracking velocimetry was developed, which is designed to measure 2-dimensional gas flow field. In this paper, influences of the swirl and tumble intensifying valves on the in-cylinder flow characteristics under the various intake flow conditions were investigated by using this PTV method. Based on the results of experiment, the generation process of swirl and tumble flow in a cylinder during intake stroke was clarified. Its effect on the tumble ratio at the end of compression stroke was also investigated.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.3 s.246
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• pp.215-221
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• 2006

A stereoscopic particle tracking velocimetry (SPTV) technique based on the 2-frame hybrid particle tracking velocimetry (PTV) method was developed. The expansion of 2D PTV to SPTV is facilitated by the fact that the PTV method tracks individual particle centroids. To evaluate the performance and measurement accuracy of the present SPTV technique, it was applied to flow images of rigid body translation and synthetic standard images of jet shear flow and impinging jet flow. The data processing routine and measurement uncertainty of the SPTV technique are compared with those of conventional stereoscopic particle image velecimet.y (SPBV). In addition, the centroid translation effect of 2D particle image velocimetry (PIV) is defined and its effect on SPIV measurements is discussed. Compared to the SPIV method, the SPTV technique has inherited merits of concise and precise velocity evaluation procedures and provides better spatial resolution and measurement accuracy.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.489-497
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• 1994

The most serious problems related to the cardiovascular prothesis are thrombosis and hemolysis. It is known that the flow pattern of cardiovascular prostheses is highly correlated with thrombosis and hemolysis. Laser Doppler Anemometry (LDA) is a usual method to get flow pattern, which is difficult to operate and has narrow measure region. Particle Image Velocimetry (PIV) can solve these problems. Because the flow speed of valve is too high to catch particles by CCD camera, high-speed camera (Hyspeed : Holland-Photonics) was used. The estimated maximum flow speed was 5m/sec and maximum trackable length is 0.5 cm, so the shutter speed was determined as 1000 frames per sec. Several image processing techniques (blurring, segmentation, morphology, etc) were used for the preprocessing. Particle tracking algorithm and 2-D interpolation technique which were necessary in making gridrized velocity pronto, were applied to this PIV program. By using Single-Pulse Multi-Frame particle tracking algorithm, some problems of PIV can be solved. To eliminate particles which penetrate the sheeted plane and to determine the direction of particle paths are these solving methods. 1-D relaxation fomula is modified to interpolate 2-D field. Parachute artificial heart valve which was developed by Seoul National University and Bjork-Shiely valve was testified. For each valve, different flow pattern, velocity profile, wall shear stress and mean velocity were obtained.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.4
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• pp.34-43
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• 2001

Analysis and control of intake charge motion such as swirl and tumble are very important to improve the performance of gasoline engines. In this paper, single frame double exposure PTV(particle tracking velocimetry) is used to investigate intake flow characteristic in a steady flow test rig of gasoline engine with 2-valve and pent-roof combustion chamber. To validate this PTV method, we confirmed reliability of this PTV method using chopper, and coaxial burner experiments. The velocity Held of intake flow is measured with the intake valve lift variation. It is shown that maximum flow velocity is increased and tumble flow become stronger than inverse tumble flow as valve lift increase.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.315-324
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• 2023

In this paper, we propose a real-time pose estimation method for a monocular camera using a particle filter integrated with UKF (unscented Kalman filter). While conventional camera tracking techniques combine camera images with data from additional devices such as gyroscopes and accelerometers, the proposed method aims to use only two-dimensional visual information from the camera without additional sensors. This leads to a significant simplification in the hardware configuration. The proposed approach is based on a particle filter integrated with UKF. The pose of the camera is estimated using UKF, which is defined individually for each particle. Statistics regarding the camera state are derived from all particles of the particle filter, from which the real-time camera pose information is computed. The proposed method demonstrates robust tracking, even in the case of rapid camera shakes and severe scene occlusions. The experiments show that our method remains robust even when most of the feature points in the image are obscured. In addition, we verify that when the number of particles is 35, the processing time per frame is approximately 25ms, which confirms that there are no issues with real-time processing.

• Journal of Navigation and Port Research
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• v.29 no.6 s.102
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• pp.509-513
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• 2005

Ship maneuverability is mainly determined according to hull-propeller-rudder system of a ship and directly related to the ship safety during the operation in the ocean. Among hull-propeller-rudder system the rudder system had direct concern with the ship maneuverability and a special rudder has been recommended to improve the ship maneuverability. In this paper the study of flapped rudder's 2-dimensional section was accomplished Model tests had been carried out with different angles of attack of a main foil and flap's deflection angles to predict the performance of the flapped rudder and the 2 frame particle tracking method had been used to obtain the velocity distribution in the flow field during model tests. $Re=1.027{\times}10^4$ had been used during the whole experiments and measured results had been compared with each other.