• Proceedings of the KSME Conference
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• 2002.08a
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• pp.507-510
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• 2002

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity Held of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. Flows size is $1500{\times}100{\times}180(mm)$, particle is Nylon12(1mm) and illuminator is Hollogen type lamp(100w). The stereo photogrammetry is adopted for the three dimensional geometrical mesurement of tracer particle. For the stereo-pair matching, the camera parameters should be decide in advance by a camera calibration. Camera parameter calculation equation is collinearity equation. In order to calculate the particle 3-D position based on the stereo photograrnrnetry, the eleven parameters of each camera should be obtained by the calibration of the camera. Epipolar line is used for stereo pair matching. The 3-D position of particle is calculated from the three camera parameters, centers of projection of the three cameras, and photographic coordinates of a particle, which is based on the collinear condition. To find velocity vector used 3-D position data of the first frame and the second frame. To extract error vector applied continuity equation. This study developed of various 3D-PIV animation technique.

• Journal of ILASS-Korea
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• v.10 no.3
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• pp.17-28
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• 2005

The Holographic Particle Velocimetry system can be a promising optical tool for the measurements of three dimensional particle velocities. In this study, diffused illumination holographic system to measure the sizes and 3D velocities of moving particles based on automatic image processing was developed. First of all basic optical systems for pulse laser recording, continuous laser reconstruction, and image acquisition, were constructed. To determine the position of particles in the optical axis, new three auto-focusing parameters(AEP), namely, Correlation Coefficient, Sharpness Index, and Depth Intensity were introduced and verified. The developed system was applied to spray droplets to validate the capability of the system. Three dimensional positions of particles viewed from two sides were decided using AFP and then 3D velocities of Particles were extracted by particle tracking algorithm. Comparison of measurement results of sizes and 3D velocities of particles with those obtained by laser instrument, PDPA, showed good consistency of the developed holographic system.

• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.100-107
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• 2001

A simple new technique of particle depth position measurement, which can be applied for three-dimensional velocity measurement of fluid flows, is proposed. Two color illumination system that intensity is encoded as a function of z-coordinate is introduced. A calibration procedure is described and a profile of small sphere is detected by using the present method as preliminary test. Then, this method is applied to three-dimensional velocity field measurement of simple flow fields seeded with tracer particles. The motion of the particles is recorded by color 3CCD camera. The particle position in the image plane is read directly from the recorded image and the depth of each particle is measured by calculation of the intensity ratio of encoded two color illumination. Therefore three-dimensional velocity components are reconstructed. Although the result includes to some extent error, the feasibility of the present technique for three-dimensional velocity measurement was confirmed.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.71-76
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• 2022

In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.102-109
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• 2014

A particle system is used for modeling the physical phenomenon. There are many traditional ways for simulation modeling which can be well suited for application including the landscapes of branches, clouds, waves, fog, rain, snow and fireworks in the three-dimensional space. In this paper, we present a new fireworks modeling technique for modeling 3D firework based on Firework Particle Tracking (FPT) using the particle system. Our method can track and recognize the launched and exploded particle of fireworks, and extracts relatively accurate 3D positions of the particles using 3D depth values. It can realize 3D simulation by using tracking information such as position, speed, color and life time of the firework particle. We exploit Region of Interest (ROI) for fast particle extraction and the prevention of false particle extraction caused by noise. Moreover, Kalman filter is used to enhance the robustness in launch step. We propose a new fireworks particle tracking method for the efficient tracking of particles by considering maximum moving range and moving direction of particles, and shall show that the 3D speeds of particles can be obtained by finding the rotation angles of fireworks. Also, we carry out the performance evaluation of particle tracking: tracking speed and accuracy for tracking, classification, rotation angle respectively with respect to four types of fireworks: sphere, circle, chrysanthemum and heart.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.300-306
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• 2023

A hull-cleaning robot sticks to the surface of a vessel and moves for efficient cleaning. Precise path planning and tracking using the current position is crucial. Many robots rely on the INS algorithm, but errors accumulate. To fix this, GPS, sonar, and USBL are used, though with limitations. Selecting suitable sensors for the surface operation and accurate positioning algorithm are vital. In this study, we developed a robot position estimation algorithm using the structure of a ship. Problems that arise when expanding the 2D position estimation algorithm used in existing wall structures to 3D were evaluated and methods for solving them were proposed. In addition, we aimed to improve performance by deriving singularities that exist in the robot path and proposing an error correction algorithm based on the singularities.

• Journal of the Korean institute of surface engineering
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• v.41 no.5
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• pp.205-213
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• 2008

A 3D particle code is developed to analyze electron behavior in a planar magnetron sputtering cathode either in balanced or unbalanced configuration. Three types of collisions are included; electron - neutral elastic, excitation to a metastable state and ionization. Flight path is calculated by a 4-th order Runge-Kutta method with a time step of 10 ps. Effects of electron starting position, magnetic field intensity and configuration were analyzed. For a more efficient and accurate modeling, multithreading technique is considered for multicore CPU computers. Under an assumption of cold ion approach, target erosion profiles are predicted for a flat target surface.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.352-361
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• 2018

This paper proposes a sensing system of the Halbach array permanent magnet spherical motor(PMSM). The rotor position can be obtained by solving three rotation angles, which revolves around 3 reference axes of the stator. With the development of 3-D hall sensor, the position identification problem of the Halbach array PMSM based on rotor magnetic field is studied in this paper. A nonlinear and serious coupling relationship between the rotation angles and the measured magnetic flux density is established on the basis of the rotation transformation theory and the magnetic field model. In order to get rid of the influence on position detection caused by the harmonics of rotor magnetic field and the stator coil magnetic field, a sensor location combination scheme is proposed. In order to solve the nonlinear equation fast and accurately, a new position solution algorithm which combines the merits of gradient projection and particle swarm optimization(PSO) is presented. Then the rotation angles are obtained and the rotor position is identified. The validity of the sensing system is verified through the simulation.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.123-131
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• 2020

This study proposes a real-time rendering algorithm for lighting when each of more than 100,000 moving particles exists as a light source. Two 3D textures are used to dynamically determine the range of influence of each light, and the first 3D texture has light color and the second 3D texture has light direction information. Each frame goes through two steps. The first step is to update the particle information required for 3D texture initialization and rendering based on the Compute shader. Convert the particle position to the sampling coordinates of the 3D texture, and based on this coordinate, update the colour sum of the particle lights affecting the corresponding voxels for the first 3D texture and the sum of the directional vectors from the corresponding voxels to the particle lights for the second 3D texture. The second stage operates on a general rendering pipeline. Based on the polygon world position to be rendered first, the exact sampling coordinates of the 3D texture updated in the first step are calculated. Since the sample coordinates correspond 1:1 to the size of the 3D texture and the size of the game world, use the world coordinates of the pixel as the sampling coordinates. Lighting process is carried out based on the color of the sampled pixel and the direction vector of the light. The 3D texture corresponds 1:1 to the actual game world and assumes a minimum unit of 1m, but in areas smaller than 1m, problems such as stairs caused by resolution restrictions occur. Interpolation and super sampling are performed during texture sampling to improve these problems. Measurements of the time taken to render a frame showed that 146 ms was spent on the forward lighting pipeline, 46 ms on the defered lighting pipeline when the number of particles was 262144, and 214 ms on the forward lighting pipeline and 104 ms on the deferred lighting pipeline when the number of particle lights was 1,024766.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.410-416
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• 2001

An algorithm of 3-D particle image velocimetry(3D-PIV) was developed for the measurement of 3-D velocity field of complex flows. The measurement system consists of two or three CCD camera and one RGB image grabber. In this study, stereo photogrammetty was applied for the 3-D matching of tracer particles. Epipolar line was used to decect the stereo pair. 3-D CFD data was used to estimate algorithm. 3-D position data of the first frame and the second frame was used to find velocity vector. Continuity equation was applied to extract error vector. The algorithm result involved error vecotor of about 0.13 %. In Pentium III 450MHz processor, the calculation time of cross-correlation for 1500 particles needed about 1 minute.