• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.135-142
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• 2018

In recent years, researches utilizing UAV for military purposes such as precision tracking and batting have been actively conducted. In order to track the preceding flight, there has been a previous research on estimating the attitude information of the flight such as roll, pitch, and yaw using images taken from the rear UAV. In this study, we propose a method to estimate the attitude information more precisely by applying the Kalman filter to the existing image processing technique. By applying the Kalman filter to the estimated attitude data using image processing, we could reduce the estimation error of the attitude angle significantly. Through the simulation experiments, it was confirmed that the estimation using the Kalman filter can estimate the posture information of the aircraft more accurately.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.750-757
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• 2020

One of the basic tasks for robots to interact with humans is to quickly and accurately grasp human behavior. Therefore, it is necessary to increase the accuracy of human pose recognition when the robot is estimating the human pose and to recognize it as quickly as possible. However, when the human pose is estimated using deep learning, which is a representative method of artificial intelligence technology, recognition accuracy and speed are not satisfied at the same time. Therefore, it is common to select one of a top-down method that has high inference accuracy or a bottom-up method that has high processing speed. In this paper, we propose two methods that complement the disadvantages while including both the advantages of the two methods mentioned above. The first is to perform parallel inference on the server using multi GPU, and the second is to mix bottom-up and One-class Classification. As a result of the experiment, both of the methods presented in this paper showed improvement in speed. If these two methods are applied to the entertainment robot, it is expected that a highly reliable interaction with the audience can be performed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.291-292
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• 2019

본 논문에서는 자세 교정에 도움을 줄 수 있는 압력센서 기반의 스마트 방석 개발 사례를 소개한다. 스마트 방석은 스마트폰과 블루투스로 연결되며 스마트폰 앱은 사용자의 자세 정보를 분석한 후 자세가 불안정한 징후가 판단되면 알림을 통해 바람직한 자세를 취할 수 있도록 안내한다. 본 시제품 개발에서는 압력센서의 값을 분석한 후 단순한 형태의 자세 추정 방식을 채택하였지만 향후 다양한 실험 및 딥러닝 응용을 통해 정확한 자세 추정을 위한 알고리즘을 개발할 계획이며 알림에 의한 수동적 자세 교정이 아닌 기구 설계, 모터 제어 등을 통해 능동적인 자세 교정을 지원하는 스마트 방석을 개발할 계획이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.558-567
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• 2017

In this research, we developed an efficient real-time human exercise pose estimation system using multiple Kinects. The main objective of this system is to measure and recognize the user's posture (such as knee curl or lunge) more accurately by employing Kinects on the front and the sides. Especially it is designed as an extensible and modular method which enables to support various additional postures in the future. This system is configured as multiple clients and the Unity3D server. The client processes Kinect skeleton data and send to the server. The server performs the multiple-Kinect calibration process and then applies the pose estimation algorithm based on the Kinect-based posture recognition model using feature extractions and the weighted averaging of feature values for different Kinects. This paper presents the design and implementation of the human exercise pose estimation system using multiple Kinects and also describes how to build and execute an interactive Unity3D exergame.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.469-475
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• 2015

This paper describes about the method for designing an extended Kalman filter to accurately measure the position of the spatial-phase system using a semiconductor sensor. Spatial position is expressed by the correlation of the rotated coordinate system attached to the body from the inertia coordinate system (a fixed coordinate system). To express the attitude, quaternion was adapted as a state variable, Then, the state changes were estimated from the input value which was measured in the gyro sensor. The observed data is the value obtained from the acceleration sensor. By matching between the measured value in the acceleration sensor and the predicted calculation value, the best variable was obtained. To increase the accuracy of estimation, designation of the extended Kalman filter was performed, which showed excellent ability to adjust the estimation period relative to the sensor property. As a result, when a three-axis gyro sensor and a three-axis acceleration sensor were adapted in the estimator, the RMS(Root Mean Square) estimation error in simulation was retained less than 1.7[$^{\circ}$], and the estimator displayed good property on the prediction of the state in 100 ms measurement period.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1931-1932
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• 2006

로봇이 어떤 물체를 인지하고 그 물체에 대해 어떤 작업을 하고자 할 때 특정 물체의 인식 문제, 3차원 정보를 획득하는 문제, 자세를 추정하는 문제 등 해결해야 될 문제들이 있다. 물체를 인식하는 과정에서는 주위 배경과 물체의 크기의 변화, 회전, 가려짐 등으로 인해 물체 인식을 어렵게 만드는 요소들이 있다. 2차원 이미지를 통해 3차원 정보를 추출하는 과정은 일반적으로 두 대의 카메라를 이용하여 스테레오 이미지를 통해 얻는다. 이 때 좌우 영상간의 매칭의 과정이 필요하다. 자세 추정의 문제는 카메라 좌표와 물체의 좌표간의 관계를 알아야 한다. Visual Servoing을 어렵게 만드는 많은 요인들이 있으며 본 논문에서는 물체의 크기, 회전, 이동에 불변인 디스크립터(descriptor)를 사용하는 SIFT(Scale Invariant Feature Transform)를 통해 3차원 물체의 인식과 자세를 추정하는 방법을 제시한다. 또한 자세 추정을 위해 2차원 Keypoint들의 매칭을 3차원 정보를 통해 검증하는 방법을 제시한다. (SIFT에 의해 추출된 point를 Keypoint라 명한다.)

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.65-70
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• 2005

Incorrect ambiguity integer of GPS make a large error on attitude determination. In this paper one method is suggested for estimating the multipath of GPS carrier measurement while attitude determination. The multi-antenna system consists of 4 antennas have the same clock error help to make attitude determination effectively. If the distance between antennas is a half wavelength, it is not necessary to search the ambiguity integer and the multipath of GPS carrier measurement can be estimated. The results of the simulation are shown and analyzed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.105-106
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• 2018

본 논문에서는 동적 프로젝션 맵핑을 구현하기 위하여 3차원 공간의 깊이 정보와 대상 객체의 색상영상에서의 특징점을 추출하여 3차원 공간상에서 움직이는 2차원 평면 객체의 자세를 안정적으로 추정하는 기법을 제안한다. 제안 기법은 타겟 이미지를 출력하여 타겟 이미지 보다 큰 평면 패널에 부착하고, 이 평면 패널을 3차원 공간상에서 움직이는 환경에서 타겟 이미지의 자세를 안정적으로 추정하기 위하여 고안되었다. 제안 기법에서는 우선 패널이 움직일 수 있는 깊이 영역을 지정하여 해당 깊이 영역에 존재하는 2차원 패널을 추출하고, 패널의 사각영역을 추출한다. 또한, 색상 영상에 SURF 알고리즘을 적용하여 2차원 평면상에 부착된 타겟 이미지의 영역을 색상 특징을 기반으로 함께 추출하여 패널의 사각 영역과 타겟 이미지의 상대적인 위치 정보를 추출한다. 셋업 단계에서 추출된 타겟 이미지의 상대적인 위치 정보를 이용하여, 조명의 변화에 의하여 순간적으로 타겟 이미지의 특징점 추적에 실패한 경우, 패널의 사각 영역에 의해 계산된 타겟 이미지의 상대적 위치 정보를 계산하여 자세 추정에 사용함으로써 움직이는 타겟 이미지의 3차원 자세를 안정적으로 추정할 수 있도록 하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.7
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• pp.680-687
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• 2008

This paper presents map creation algorithm and initial attitude estimation method for the proposed optical head tracker system. The optical head tracker system consists of the IR stereo cameras and infrared LEDs as features on the helmet. In order for the stereo camera to track the luminous LEDs, it must take in to account the light radiation from the LEDs to determine the position of the center points. The proposed map creation algorithm makes map data about the position of features center points on the helmet frame. Also, initial attitude estimation method is proposed to estimate the initial attitude and position of a pilot head from the camera frame by the use of the feature pattern on the helmet. Therefore, the head motion can be expressed with respect to the body frame of a flight.

• 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.