• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.439-448
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• 2020

In this paper, we propose a modified optimization algorithm for point cloud matching of multi-view RGB-D cameras. In general, in the computer vision field, it is very important to accurately estimate the position of the camera. The 3D model generation methods proposed in the previous research require a large number of cameras or expensive 3D cameras. Also, the methods of obtaining the external parameters of the camera through the 2D image have a large error. In this paper, we propose a matching technique for generating a 3D point cloud and mesh model that can provide omnidirectional free viewpoint using 8 low-cost RGB-D cameras. We propose a method that uses a depth map-based function optimization method with RGB images and obtains coordinate transformation parameters that can generate a high-quality 3D model without obtaining initial parameters.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.881-888
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• 2020

In this paper, research on estimation of states of a target of interest using Line Of Sight(LOS) angle measurement is performed. Target's position, velocity, and acceleration are chosen to be the states of interests. The LOS measurement is known to be highly non-linear, making target dynamic modeling hard to be implemented into a filter. To solve this issue, the Pseudomeasurement equation was applied to the LOS measurement equation. With the help of this equation, 3D variable turn target dynamic model is applied to the filter model. For better performance, Kinematic Constraint is also implemented into the filter model. As for the filter, Bias Compensation Pseudomeasurement Filter (BCPMF) is used which is known for its robustness to initial conditions. Moreover, Two-Stage Kalman Filter (TSKF) form was also implemented to benefit from the parallel computation. As a result, TBCPMF 3DVT-KC is proposed and simulated to assess performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.568-576
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• 2003

This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.47-55
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• 2012

In this paper, we propose a method to reconstruct accurate 3D shape object by using multi-view images which are disturbed by motion blur. In multi-view deblurring, more precise PSF estimation can be done by using the geometric relationship between multi-view images. The proposed method first estimates initial 2D PSFs from individual input images. Then 3D PSF candidates are projected on the input images one by one to find the best one which are mostly consistent with the initial 2D PSFs. 3D PSF consists with direction and density and it represents the 3D trajectory of object motion. 야to restore 3D shape by using multi-view images computes the similarity map and estimates the position of 3D point. The estimated 3D PSF is again projected to input images and they replaces the intial 2D PSFs which are finally used in image deblurring. Experimental result shows that the quality of image deblurring and 3D reconstruction improves significantly compared with the result when the input images are independently deblurred.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.521-532
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• 2014

ATSC-M/H based hybrid 3DTV, which is one of the service compatible 3DTV system, has considerable quality gap between the left and right views. And CRA(Conditional Replenishment Algorithm) has been proposed to deal with the issue of resolution mismatch and improve the visual quality. In CRA, the disparity vectors of stereoscopic images are estimated. The disparity compensated left view and simply enlarged right view are compared and conditionally selected for generating the enhanced right view. In order to implement CRA, a fast algorithm is strongly required because the disparity vectors need to be obtained at every layer and the complexity of CRA is quite high. In this paper, we adopted SDSP(Small Diamond Search Pattern) instead of full search and predicted the initial position of search pattern by examining the spatio-temporal correlation of disparity vectors and also suggested the SKIP mode to limit the number of processing units. The computer simulation showed that the proposed fast algorithm could greatly reduce the processing time while minimizing the quality degradation of reconstructed right view.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.502-517
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• 2019

Global warming and rapid climate change have long affected the characteristics of typhoons in the Northwest Pacific, which has induced increasing devastating disasters along the coastal regions of the Korean peninsula. Synthetic Aperature Radar (SAR), as one of the microwave sensors, makes it possible to produce high-resolution sea surface wind field around the typhoon under cloudy atmospheric conditions, which has been impossible to obtain the winds from satellite optical and infrared sensors. The Geophysical Model Functions (GMFs) for sea surface wind retrieval from SAR data requires the input of wind direction, which should be based on the accurate estimation of the center of the typhoon. This study estimated the typhoon centers using Sentinel-1A images to improve the problem of typhoon center detection method and to reflect it in retrieving the sea surface wind. The results were validated by comparing with the typhoon best track data provided by the Korea Meteorological Administration (KMA) and Japan Meteorological Agency (JMA), and also by using infrared images of Himawari-8 satellite. The initial center position of the typhoon was determined by using VH polarization, thereby reducing the possibility of error. The detected center showed a difference of 23.76 km on average with the best track data of the four typhoons provided by the KMA and JMA. Compared to the typhoon center estimated by Himawari-8 satellite, the results showed an average spatial variation of 11.80 km except one typhoon located near land with a large difference of 58.73 km. This result suggests that high-resolution SAR images can be used to estimate the center and retrieve sea surface wind around typhoons.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.455-464
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• 2019

The sensorless control based on the flux linkage of PM synchronous motors has excellent position estimation characteristics at low speeds. However, a limitation arises because the integrator of flux estimator is saturated by the DC offset generated during the analog to digital conversion(ADC) process of the measured current. In order to overcome this limitation, HPF with a low cutoff frequency is used. However, the estimation performance is deteriorated (Ed- the verb deteriorate already includes the meaning of 'problem') at high speed due to the low cutoff frequency, and increasing the cutoff frequency of the HPF induces further problems of phase leading and initial starting failure at low speeds. In this paper, the cutoff frequency of HPF was synchronized to the operation frequency of the motor: at low speeds the cutoff frequency was set to low in order to reduce the phase leading of the estimated flux, and at high speeds it was set to high to raise the DC offset removal performance. As a result, the operating range was increased by 200%. Furthermore, a phase compensation algorithm is proposed to reduce the phase leading of the HPF to less than 1.5 degrees over the full operating range. The proposed sensorless control algorithm was verified by experiment with a PM synchronous motor for a washing machine.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.581-588
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• 2020

This study examined a brake pad wear compensation method for an Electro-Mechanical Brake (EMB) using the braking test device. A three-phase Interior Permanent Magnet Synchronous Motor (IPMSM) was applied to drive the actuator of an EMB. Current control, speed control, and position control were used to control the clamping force of the EMB. The wear compensation method was performed using a software algorithm that updates the motor model equation by comparing the motor output torque current with a reference current. In addition, a simple first-order motor model equation was applied to estimate the output clamping force. The operation time to the maximum clamping force increased within 0.1 seconds compared to the brake pad in its initial condition. The experiment verified that the reference operating time was within 0.5 seconds, and the maximum value of the clamping force was satisfied under the wear condition. The wear compensation method based on the software algorithm in this paper can be performed in the pre-departure test of rolling stock.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.84-91
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• 2009

This paper presents an online partial 3D modeling methodology that uses a mobile augmented reality system and aerial photographs, and a tracking methodology that compares the 3D model with a video image. Instead of relying on models which are created in advance, the system generates a 3D model for a real building on the fly by combining frontal and aerial views. A user's initial pose is estimated using an aerial photograph, which is retrieved from a database according to the user's GPS coordinates, and an inertial sensor which measures pitch. We detect edges of the rooftop based on Graph cut, and find edges and a corner of the bottom by minimizing the proposed cost function. To track the user's position and orientation in real-time, feature-based tracking is carried out based on salient points on the edges and the sides of a building the user is keeping in view. We implemented camera pose estimators using both a least squares estimator and an unscented Kalman filter (UKF). We evaluated the speed and accuracy of both approaches, and we demonstrated the usefulness of our computations as important building blocks for an Anywhere Augmentation scenario.