• 센서학회지
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• 제32권5호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.296-300
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• 1996

This paper presents 3D position estimation algorithm with the images of 2D vision sensors which issues Red Laser Slit light and recieves the line images. Since the sensor usually measures 2D position of corner(or edge) of a body and the measured point is not fixed in the body, the additional information of the corner(or edge) is used. That is, corner(or edge) line is straight and fixed in the body. For the body which moves in a plane, the Transformation matrix between the body coordinate and the reference coordinate is analytically found. For the 3D motion body, linearization technique and least mean squares method are used.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.171-174
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• 2003

In this paper, we propose the method of stereo images composition using adaptive dense disparity estimation. For the correct composition of stereo image and 3D virtual object, we need correct marker position and depth information. The existing algorithms use position information of markers in stereo images for calculating depth of calibration object. But this depth information may be wrong in case of inaccurate marker tracking. Moreover in occlusion region, we can't know depth of 3D object, so we can't composite stereo images and 3D virtual object. In these reasons, the proposed algorithm uses adaptive dense disparity estimation for calculation of depth. The adaptive dense disparity estimation is the algorithm that use pixel-based disparity estimation and the search range is limited around calibration object.

• 대한의용생체공학회:의공학회지
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• 제12권1호
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• pp.49-56
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• 1991

In this paper, a method for camera position estimation in gasher using elechoendoscopic image sequence is proposed. In orders to obtain proper image sequences, the gasser in divided into three sections. It Is presented thats camera position modeling for 3D information extvac lion and image distortion due to the endoscopic lenses is corrected. The feature points are represented with respect to the reference coordinate system below 10 percents error rate. The faster distortion correction algorithm is proposed in this paper. This algorithm uses error table which is faster than coordinate transform method using n -th order polynomials.

• 센서학회지
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• 제32권4호
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• pp.232-237
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• 2023

This paper presents a system for estimating the position of a magnet using a magnetic sensor. An algorithm is presented to analyze the waveform and output voltage values of the magnetic field generated at each position when the magnet moves and to estimate the position of the magnet based on the analyzed data. Here, the magnet is sufficiently small to be inserted into a blood vessel and has a micro-magnetic field of hundreds of nanoteslas owing to the small size and shape of the guide wire. In this study, a highly sensitive magneto-impedance (MI) sensor was used to detect these micro-magnetic fields. Nine MI sensors were arranged in a 3×3 configuration to detect a magnetic field that changes according to the position of the magnet through the MI sensor, and the voltage value output was polynomially regressed to specify a position value for each voltage value. The accuracy was confirmed by comparing the actual position value with the estimated position value by expanding it from a 1D straight line to a 3D space. Additionally, we could estimate the position of the magnet within a 3% error.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.167-170
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• 2000

In this paper, we present a fast algorithm for the motion estimation using the efficient selection of an initial search position. In the method, we select the initial search position using the motion vector from the subsmpled images, the predicted motion vector from the neighbor blocks, and the (0,0) motion vector. While searching the candidate blocks, we use the spiral search pattern with the successive elimination algorithm(SEA) and the partial distortion elimination(PDE). The experiment results show that the complexity of the proposed algorithm is about 2∼3 times faster than the three-step search(TSS) with the PSNR loss of just 0.05［dB］∼0.1［dB］ than the full search algorithm PSNR. The search complexity can be reduced with quite a few PSNR loss by controling the number of the depth in the spiral search pattern.

• 한국통신학회논문지
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• 제15권12호
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• pp.1002-1016
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• 1990

본 논문은 스테레오비젼 시스템을 설계 제작하고, 제작된 시스템을 가지고 3차원 이동물체의 변위평가 방법을 제안하였다. 이동물체의 추출은 차영상 알고리즘에 의해 추출하고, 3차원 이동물체의 기하학적인 위치좌표는 2개의 2차원 물체의 면적중심을 합성시켜 구하였다. 3차원 이동물체의 범위평가는 합성된 3차원 좌표값에 의해서 물체의 이동속도 및 거리, 이동궤적, 카메라와 물체 사이의 공간거리를 산출하여 입증하였다.

• 대한전자공학회논문지SP
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• 제39권3호
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• pp.23-35
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• 2002

시선 위치 추적이란 모니터상에 사용자가 쳐다보고 있는 지점을 파악해 내는 기술이다 이 논문에서는 컴퓨터 비젼 방법을 이용하여 사용자가 모니터 상에 어느 지점을 쳐다보고 있는지를 파악(시선 위치 추적)하는 새로운 방법을 제안한다. 시선위치를 파악하기 위해 본 논문에서는 얼굴 영역 및 얼굴 특징점(양 눈, 양 콧구멍, 입술 끝점 등)을 2차원 카메라 영상으로부터 추출하였으며, 이들의 움직임으로부터 카메라 보정 및 매개변수 추정 방법등을 이용하여 초기 3차원 위치를 추정해 내었다. 이후 모니터 상의 한 지점을 쳐다보기 위해 사용자가 얼굴을 움직이는 경우 이러한 얼굴의 3차원 움직임 량 역시 자동으로 추정하였다. 이로부터 변화된 얼굴 특징점의 3차원 위치를 계산해 낼 수 있었으며, 이를 바탕으로 모니터 상의 시선 위치를 구하였다. 실험 결과, 19인치 모니터상의 임의의 지점을 사용자가 쳐다보았을 때, 약 2.01인치의 시선 위치에러 성능을 얻었다.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.232-238
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• 2020

In this paper, we study on aerial objects detection and position estimation algorithm for the safety of UAV that flight in BVLOS. We use the vision sensor and LiDAR to detect objects. We use YOLOv2 architecture based on CNN to detect objects on a 2D image. Additionally we use a clustering method to detect objects on point cloud data acquired from LiDAR. When a single sensor used, detection rate can be degraded in a specific situation depending on the characteristics of sensor. If the result of the detection algorithm using a single sensor is absent or false, we need to complement the detection accuracy. In order to complement the accuracy of detection algorithm based on a single sensor, we use the Kalman filter. And we fused the results of a single sensor to improve detection accuracy. We estimate the 3D position of the object using the pixel position of the object and distance measured to LiDAR. We verified the performance of proposed fusion algorithm by performing the simulation using the Gazebo simulator.

• 제어로봇시스템학회논문지
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• 제18권1호
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• pp.7-12
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• 2012

In this paper, we present an effective viewpoint estimation algorithm for the Moving parallax barrier method of 3D display mobile device. Moving parallax barrier is designed to overcome the biggest problem, the limited view angle. To accomplish it, the position of the viewer's eyes or face should be estimated with strong stability and no latency. We focus on these requirements in the poor performance of mobile processors. We used a pre-processing algorithm in order to overcome the various illumination changes. And, we combined the conventional Viola-Jones face detection method and Optical-flow algorithm for robust and stable viewpoint estimation. Various computer simulations prove the effectiveness of the proposed method.