• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.9-14
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• 2019

A small millimeter-wave tracking radar is a pulse-based radar that searches, detects, and tracks a target in real time through a TWS (Track While Scan) method for a traps target on the sea with a large RCS running at low speed. It is necessary to develop a board equipped with a high-speed CPU to acquire and track target information through LPRF, DBS, and HRR signal processing techniques for a trap target operating various kinds of dexterous objects such as chaff and decoy, We designed a signal processor structure including DFT (Discrete Fourier Transform) module design that can perform real - time FFT operation using FPGA (Field Programmable Gate Array) and verified the signal processor implemented through performance test.

• Journal of Astronomy and Space Sciences
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• v.36 no.1
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• pp.35-43
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• 2019

The Optical Wide-field patroL-Network (OWL-Net) is a global optical network for Space Situational Awareness in Korea. The primary operational goal of the OWL-Net is to track Low Earth Orbit (LEO) satellites operated by Korea and to monitor the Geostationary Earth Orbit (GEO) region near the Korean peninsula. To obtain dense measurements on LEO tracking, the chopper system was adopted in the OWL-Net's back-end system. Dozens of angle-only measurements can be obtained for a single shot with the observation mode for LEO tracking. In previous work, the reduction process of the LEO tracking data was presented, along with the mechanical specification of the back-end system of the OWL-Net. In this research, we describe an integrity assessment method of time-position matching and verification of results from real observations of LEO satellites. The change rate of the angle of each streak in the shot was checked to assess the results of the matching process. The time error due to the chopper rotation motion was corrected after re-matching of time and position. The corrected measurements were compared with the simulated observation data, which were taken from the Consolidated Prediction File from the International Laser Ranging Service. The comparison results are presented in the In-track and Cross-track frame.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.78-87
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• 2012

In this paper, we address the tracking problem caused by camera motion and rolling shutter effects associated with CMOS sensors in consumer handheld cameras, such as mobile cameras, digital cameras, and digital camcorders. A modified particle filtering method is proposed for simultaneously tracking objects and compensating for the effects of camera motion. The proposed method uses an elastic registration algorithm (ER) that considers the global affine motion as well as the brightness and contrast between images, assuming that camera motion results in an affine transform of the image between two successive frames. By assuming that the camera motion is modeled globally by an affine transform, only the global affine model instead of the local model was considered. Only the brightness parameter was used in intensity variation. The contrast parameters used in the original ER algorithm were ignored because the change in illumination is small enough between temporally adjacent frames. The proposed particle filtering consists of the following four steps: (i) prediction step, (ii) compensating prediction state error based on camera motion estimation, (iii) update step and (iv) re-sampling step. A larger number of particles are needed when camera motion generates a prediction state error of an object at the prediction step. The proposed method robustly tracks the object of interest by compensating for the prediction state error using the affine motion model estimated from ER. Experimental results show that the proposed method outperforms the conventional particle filter, and can track moving objects robustly in consumer handheld imaging devices.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.773-777
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• 2016

In this paper, a novel multi-object tracking method to track an unknown number of objects is proposed. To handle multiple object states and uncertain observations efficiently, a probability hypothesis density (PHD) filter is adopted and modified. The PHD filter is capable of reducing false positives, managing object appearances and disappearances, and estimating the multiple object trajectories in a unified framework. Although the PHD filter is robust in cluttered environments, it is vulnerable to false negatives. For this reason, we propose to exploit local observations in an RFS of the observation model. Each local observation is generated by using an online trained object detector. The main purpose of the local observation is to deal with false negatives in the PHD filtering procedure. The experimental results demonstrated that the proposed method robustly tracked multiple objects under practical situations.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.33-42
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• 2013

This paper describes a multiple vehicle tracking algorithm using an integrated probabilistic data association filter (IPDAF) in urban environments. The algorithm consists of two parts; a pre-processing stage and an IPDA tracker. In the pre-processing stage, measurements are generated by a feature extraction method that manipulates raw data into predefined geometric features of vehicles as lines and boxes. After that, the measurements are divided into two different objects, dynamic and static objects, by using information of ego-vehicle motion. The IPDA tracker estimates not only states of tracks but also existence probability recursively. The existence probability greatly assists reliable initiation and termination of track in cluttered environment. The algorithm was validated by using experimental data which is collected in urban environment by using single laser scanner.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.839-844
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• 2011

Various technologies such as infrared light, ultrasonic waves, RFID, GPS, UWB, and signal indicators have been incorporated in the location tracking system. However, such pre-existing systems require location recognition in shadow areas. This study proposes a location tracking system that utilizes Cooperative Spectrum Sensing. Cooperative Spectrum Sensing is not only able to track the location and path of moving objects but also recognize when objects breakaway from the path set by sensors and guide them back. In addition, it has the advantage of being more efficient in terms of frequency usage. It is able to automatically fix power transmission and frequency modulation for transmission cognitive users to an optimum level within the range that does not cause interference for primary users.

• Journal of the Korean Society of Costume
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• v.18
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• pp.167-181
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• 1992

This study was conducted to clarify the formativeness of Cezanne's painting and it's influence on the Modern Fashion. Recently, fashion was introduced and applied the originality of paintings into the fabric and fashion designing. To go with the current of the times I already discussed about the Modern Fashion under the influence of the color of Impressionism and N대-Impressionism in the previous paper. In this study, Cezanne's painting and it's influence on the Modern fashion was investigated. As one of the original Impressionist, Paul Cez anne had been so adversely affected by the critical attack on his contributions to the 1874 and 1877 exhibitions that he never again showed with the group. That is, he was the first Impressionist to become dissatisfied with the superficial recording of atmospheric effects. When he turned to nature, it was not simply to depict the objects that occupied a given site but rather to consider relationships among those objects. Cezanne attempted to track down the fundamental laws of geometrical prototypes of sphere, prism and corn. Color too, he found, could be employed according to principle, like the tones of a musical scale. Throughout the Modern Fashion, various forms of Bustle style dress and geometrical style dress were reappered under the influence of the Cez anne's painting technique. And the order and the unity of all nature was illuminated on the fashion's pattern.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.876-887
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• 2018

In this paper, we propose an robust CAMShift method to track stage objects with a camera. In order to solve the problem of tracking object misdetection in existing CAMShift technique, MBR region is detected to separate the background and the subject, and the subject size of the region of interest is calculated to solve the problem of erroneously detecting a large region having a similar color distribution ratio. Also, by applying the color corelogram and MB-LBP to the part that can not be solved by the color ratio and the size limitation, accurate texture tracking is enabled by reflecting the texture characteristics. Experimental results show that the proposed method has good tracking performance for objects that do not deviate from the size of the subject set in the area of interest and accurately extracts the texture characteristics of different subjects with similar color distribution ratios.

• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.81-86
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• 2016

In this paper, we propose a simple and effective vision-based tracking controller design for autonomous object tracking using multicopter. The multicopter based automatic tracking system usually unstable when the object moved so the tracking process can't define the object position location exactly that means when the object moves, the system can't track object suddenly along to the direction of objects movement. The system will always looking for the object from the first point or its home position. In this paper, PID control used to improve the stability of tracking system, so that the result object tracking became more stable than before, it can be seen from error of tracking. A computer vision and control strategy is applied to detect a diverse set of moving objects on Raspberry Pi based platform and Software defined PID controller design to control Yaw, Throttle, Pitch of the multicopter in real time. Finally based series of experiment results and concluded that the PID control make the tracking system become more stable in real time.