• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.177-186
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• 2017

Recently, Autonomous vehicles are getting hot attention. Amazon, the biggest online shopping service provider is developing a delivery system that uses drones. This kinds of platforms are need accurate attitude information for navigation. In this paper, a structure design of AHRS using low-cost inertia sensor is proposed. To estimate attitudes a Kalman filter which uses a quaternion based dynamic model, bias-removed measurements from MEMS Gyro, raw measurements from MEMS accelerometer and magnetometer, is designed. To remove bias from MEMS Gyro, an additional Kalman filter which uses raw Gyro measurements and attitude estimates, is designed. The performance of implemented AHRS is compared with high price off-the-shelf 3DM-GX3-25 AHRS from Microstrain. The Gyro bias was estimated within 0.0001[deg/s]. And from the estimated attitude, roll and pitch angle error is smaller than 0.2 and 0.3 degree. Yaw angle error is smaller than 6 degree.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.179-185
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• 2015

Although an accelerometer is a sensor that measures acceleration, it cannot be used by itself to measure the acceleration when the orientation of the sensor changes. This paper introduces a Kalman filter for the estimation of a sensor acceleration based on a six-axis inertial sensor (i.e., a three-axis accelerometer and three-axis gyroscope). The novelty of the proposed Kalman filter lies in the fact that its state vector includes not only the tilt angle variable but also the sensor acceleration. Thus, the filter can explicitly estimate the latter with a high accuracy. The accuracy of acceleration estimates were validated experimentally under three different dynamic conditions, using an optical motion capture system. It could be concluded that the performance of the proposed Kalman filter was comparable to that of the state-of-the-art estimation algorithm employed by the Xsens MTw. The proposed algorithm may be more suitable than inertial/magnetic sensor-based algorithms for various applications adopting six-axis inertial sensors.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.923-932
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• 2017

In this paper, we propose a GRNN(: Generalized Regression Neural Network) algorithms for new eyes and face recognition identification system to solve the points that need corrective action in accordance with the existing problems of facial movements gaze upon it difficult to identify the user and. Using a Kalman filter structural information elements of a face feature to determine the authenticity of the face was estimated future location using the location information of the current head and the treatment time is relatively fast horizontal and vertical elements of the face using a histogram analysis the detected. And the light obtained by configuring the infrared illuminator pupil effects in real-time detection of the pupil, the pupil tracking was to extract the text print vector. The abstract is to be in fully-justified italicized text as it is here, below the author information.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.53-60
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• 2011

This paper proposes fusion methods of license plate detection and super-resolution for improving license plate recognition in low-resolution images. In the proposed method, we apply the license plate detection based on local structure pattern feature and the sequential super-resolution based on Kalman filter. The proposed fusion methods are divided into two according to whether the license plate is detected or not in the input image : (i) performing license plate detection after restoring whole image through super resolution, and (ii) restoring only the detected region through super-resolution after detecting the license plate. We demonstrated effectiveness of the proposed methods in various environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.111-112
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• 2017

최근 중소 테마파크들은 방문객의 감소로 인한 운영의 어려움을 겪고 있다. 새로운 어트랙션의 도입 및 테마파크의 리뉴얼을 통해 방문객 증가를 유도하기에는 천문학적인 비용이 소요된다. 이런 비용 소모는 운영 업체의 입장에서 부담하기 쉽지 않은 구조로 새로운 방법으로 방문객의 재방문률을 높일 수 있는 방안이 필요하다. 대표적인 방안으로 최근 높은 관심으로 인해 관련 기술 및 연구가 활발히 진행되고 있는 VR 시스템의 어트랙션 적용이 있다. 많은 움직임이 없고 안정적인 속도로 운영되는 어트랙션에 VR의 콘텐츠를 적용하여 사용자의 탑승률을 높이고 이로 인해 재방문률 또한 증가 시킬 수 있을 것으로 사료되어 많은 접근이 시도되고 있다. 이 논문에서는 어트랙션의 탑승자에게 몰입감 높은 VR 콘텐츠 제공을 위해 탑승한 어트랙션의 움직임과 VR영상을 동기화 하는 매칭 모듈에 대해 제안한다. 제안하는 모듈은 가속도 센서의 움직임에 따라 1차 적분하여 속도를 산출하고 이를 2차 적분하여 거리를 산출한다. 기존의 가속도 센서를 통한 이동거리 판단에는 칼만 필터를 적용한 오차 보정, 다분화 사다리꼴 적분 등의 연산이 필요하지만 본 논문의 고정 어트랙션에서는 탑승체의 방향이 결정되어 있어 최소화된 연산으로 정확한 이동거리를 판단할 수 있을 것으로 사료된다.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.424-431
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• 2020

This paper focused on the development of sports robot that detects a human player and shots a serve ball automatically. When robot technologies apply to the sports machine, the domain problems occurs such as outdoor environments and playing condition to recognize the visual and the vocal modalities. Gaussian mixture model and Kalman filter are used to detect the player's position in the left, right, and depth direction and to avoid the noises caused by the player's posture variation around the net. The sports robot is designed by the pan-tilt structure to shot a serve ball by pneumatic control under the multi layered software architecture. Finally, the proposed tracking and the machine performance are discussed by experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.601-607
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• 2006

This paper proposes a novel balance control scheme of a biped robot to predict the next position of ZMP using Kalman Filter. The mathematical model of the biped robot is generally approximated by 3D-LIPM(3D-Linear Inverted Pendulum Mode), but it cannot completely express the robot's dynamics. The stability of the biped robot depends on whether the ZMP(Zero Moment Point) position is in the stability region or out of. And the internal error between the robot mechanism and its model could affect the stability of a robot. Therefore, the proposed balance control not reduces the internal error, but also timely generates the proper control. The experiment of the proposed balance control is simulated on the virtual workspace where the biped robot may encounter with various difficulties.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.20-32
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• 2010

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.1-8
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• 2002

The color interpolation scheme can play an important role in overcoming the physical limitation of the CCD image sensor and in increasing the resolution of color signals, while most conventional approaches result in blurred edges and false color artifacts. In this paper, we have proposed an improved edge-adaptive color interpolation scheme for a progressive scan CCD image sensor with RGB color filter array The edge indicator function proposed utilizes not only the within-channel correlation but also the cross-channel correlation, and reflects the edge characteristics of an image adaptively. The color components unavailable for at each channel are interpolated along the edge direction, not across the edges, so that aliasing artifacts are supressed. Furthermore, we eliminated false color artifacts resulting from the color image formation model in the edge-adaptive color interpolation scheme by adopting the switching algorithm based on the color edge detection. Simulation results of the proposed algorithm indicate that the improved edge-adaptive color interpolation scheme produces quantitatively better and visually more pleasing results than conventional approaches.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.168-172
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• 2005

An autopilot system of a ship is very important for a safe and convenient navigation, which is realized with getting an azimuth data from a gyrocompass, a magnetic compass and a GPS(Global Positioning System) compass. Magnetic compass an azimuth error is generated by a vessel magnetism material such as steels. The magnetic pole is detected by the magnetic field sensor, it does not coincide with the true north, therefore, the detected azimuth data can not but accompany error. In this paper, in order to detect the minimum change of azimuth data which generates errors of azimuth information, a search algorithm using the Kalman Filtering method is utilized. The digital electronic compass is designed with the integration algorithm using the merits of an earth's magnetic field sensor and a GPS receiver.