• Smart Media Journal
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• v.12 no.11
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• pp.48-56
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• 2023

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.104-111
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• 2018

The sensorless control of high efficiency air compressors using a permanent magnet type synchronous motor as an oil-free air compressor is quite common. However, due to the nature of the air compressor, it is difficult to install a position sensor. In order to control the permanent magnet type synchronous motor at variable speed, the inclusion of a position sensor to grasp the position of the rotor is essential. Therefore, in order to achieve sensorless control, it is essential to use a permanent magnet type synchronous motor in the compressor. The position estimation method based on the back electromotive force, which is widely used as the sensorless control method, has a limitation in that position errors occur due either to the phase delay caused by the use of a stationary coordinate system or to the estimated back electromotive force in the transient state caused by the use of a synchronous coordinate system. Therefore, in this paper, we propose a method of estimating the position and velocity using a rotation angle tracking observer and reducing the speed ripple through a disturbance observer. An experimental apparatus was constructed using Freescale's MPU and the feasibility of the proposed algorithm was examined. It was confirmed that even if a position error occurs at a certain point in time, the position correction value converges to the actual vector position when the position error value is found.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.893-898
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• 2003

Coulomb friction is an important factor for precise position tracking control systems. The control systems with friction causes the steady state error because of being sensitive to the change of system condition and highly nonlinear characteristics. To overcome these problems, we use an estimation scheme of Coulomb friction to experiment for it's compensating. The estimated factor for Coulomb friction is used as a feed-forward compensator to improve the tracking performance of ball-screw systems. The tracking performance was improved by compensating the estimated friction torque in the feed-forward term. And, the sliding mode control which is derived from the Lyapunov stability theorem is applied for robust stability and reducing chattering. The experimental results show that the sliding mode controller with adaptive friction compensator has a good tracking performance compared with the friction uncompensated controller.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1343-1348
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• 1990

The architecture and functions of a prototype free ranging AGV system are described in this paper. The system has single tricycle configuration - the front wheel is driven and steered simultaneously. The primary position measurement device of this system is the redundant encoder system - an absolute encoder for the steering angle measurement of the front wheel, two incremental encoders for the measurement of the rear wheel rotations. The secondary position measurement device is implemented to reduce the accumulatad error in encoder measurements. The extended Kalman filter is suggested to combine the conflict measurement data for the proper position estimation.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.272-273
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• 2015

This paper analyze scenario of feeder wire fault that occurs in the AC feeding system considering train position. The fault location of AC feeding system is calculated by measuring impedance. However, in this way, estimation error can be occurred because of tie connection, boosting current, etc. Therefore, it's hard to find fault location, so that it is required to detailed circuit analysis according to fault location. We analyze the short circuit impedance values with respect to feeder wire fault according to a train position. In this paper, PSCAD is used for modeling and analysis of AC railway feeding system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.11
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• pp.979-981
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• 2013

In this paper, this study is aimed how to estimate the position of scattered pilot to be used to estimate channel in the OFDM System. The proposed method is possible to estimate the accurate position of scattered pilot to remove the phase error through cross-correlation between received signal and 4 symbol delay received signal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5219-5226
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• 2014

This paper proposes an improved scheme of pedestrian position information system using neural network theory in a GPS-disabled area. Through a learning/obtaining gait pattern and step distance about walk, run, duck walk, crab walk and crawl, the position estimation error could be minimized by rejecting the inertial navigation drift. A portable hardware module was implemented to evaluate the performance of the proposed system. The performance and effectiveness of the suggested algorithm was verified by experiments indoors.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.11
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• pp.541-547
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• 2003

Speed and torque controls of permanent magnet synchronous motors are usually attained by the application of position and speed sensors. However, speed and position sensors require the additional mounting space, reduce the reliability in harsh environments and increase the cost of a motor. Therefore, many studies have been peformed for the elimination of speed and position sensors. This paper investigates a novel speed sensorless control of a permanent magnet synchronous motor. The proposed control strategy is based on the MRAS(Model Reference Adaptive System) using the state observer model with the current error feedback and the magnet flux model as two models for the back-emf estimation. The proposed algorithm is verified through the simulation and experiment.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.19-27
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• 1998

To achieve the required services in the next-generation cellular telephone systems, the size of the cell become smaller and/or is of mixed macrocells and microcells. For more efficient system control, We make use of the mobile position and velocity information, provided that the mobility information is relatively accurate. In this paper, we propose an improved version of path-loss measurement algorithm introduced in literature[11]. The microcellular structure with severe multipath fading, reflection and refraction make mobile position and velocity estimation very difficult. In the proposed method, the pre-recorded path-loss informations, called the discrete position data base, are searched to estimate the position. Velocity estimation is obtained as a difference of the position values with respect to the time difference. Moving average filter is applied to smooth the estimated velocity and to reduce the error in the estimates. We also propose a method to simplify system implementation by reducing search area for discrete area database.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.494-504
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• 2004

The researches about gaze detection have been much developed with many applications. Most previous researches only rely on image processing algorithm, so they take much processing time and have many constraints. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.2 cm of RMS error.