• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.113-119
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• 2013

The requirement of rehabilitation is increasing from the stroke, spinal cord injury. One of the most difficult part is the upper limb rehabilitation because of its nervous complexity. A rehabilitation has effectiveness when a professional therapist treats in work at facility, but it has problems of an accessibility, a constant availability, a self-participation and taking lots of cost and time. In this paper, we test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it on the upper limb function from the 3D trajectory information which is gathered from stereo vision sensor(Kinect). From the result, PCA, ICA have low accuracy, but LDA, SVM have good accuracy to use for physical rehabilitation on the upper limb function.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.35-42
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• 2014

It is possible to improve the obstacle avoidance capability by training and recognizing the obstacles which is in certain indoor environment. We propose the technique that use underlying intensity value along with intensity map from RGB-D image which is derived from stereo vision Kinect sensor and recognize an obstacle within constant distance. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it. From the comparison experiment between RGB-D data and intensity data, RGB-D data got 4.2% better accuracy rate than intensity data but intensity data got 29% and 31% faster than RGB-D in terms of training time and intensity data got 70% and 33% faster than RGB-D in terms of testing time for LDA and SVM, respectively. So, LDA, SVM have good accuracy and better training/testing time to use for obstacle avoidance based on intensity dataset of mobile robot.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.442-450
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• 2011

A measurement system using stereo pattern recognition (SPR) method was configured to measure the rotor blade deformations and motions. An SPR-based measurement system was prepared using six stereo cameras. Through a series of experiments to evaluate the system measurement uncertainty, it was verified that the SPR system had less than 0.2mm standard uncertainty. The combined standard uncertainties for the lead-lag, flapping, and pitching motions were estimated as 0.296mm, 0.209mm, and $0.238^{\circ}$, respectively. The SPR system was installed at a general small-scaled rotor test system at Korea Aerospace Research Institute. The blade motions and elastic deformation were successfully measured under the conditions with rotating speeds of 360rpm or 589rpm, and collective pitch angles of $0^{\circ}$, $4^{\circ}$, or $6^{\circ}$. The advantages of the SPR system was analyzed in comparison with the measurement system used in Higher Harmonic Control Aeroacoustic Rotor Test -II.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.77-88
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• 1993

In this paper, we propose a stereo vision system to solve correspondence problem with large disparity and sudden change in environment which result from small distance between camera and working objects. First of all, a specific feature is divided by predfined elementary feature. And then these are combined to obtain coded data for solving correspondence problem. We use Neural Network to extract elementary features from specific feature and to have adaptability to noise and some change of the shape. Fourier transformation and Log-polar mapping are used for obtaining appropriate Neural Network input data which has a shift, scale, and rotation invariability. Finally, we use associative memory to obtain coded data of the specific feature from the combination of elementary features. In spite of specific feature with some variation in shapes, we could obtain satisfactory 3-dimensional data from corresponded codes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.81-83
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• 2014

본 논문은 HD 해상도의 고화질 방송카메라(회전과 줌이 가능한)와 '키넥트' 같은 범용 모션인식 카메라를 연동하여 방송용 모션기반 증강현실 어플리케이션을 구현하기 위해서, 연기자의 위치를 가상 월드 좌표로 자동 변환시키는 방법을 제안한다. 방송환경에서 키넥트와 같은 모션인식카메라(RGB-D 카메라)를 사용하기 위해서는 거리와 조명의 영향을 많이 받아 연기자와 가까운 천장이나 카메라 밑처럼 그 설치 위치가 제약되곤 한다. 이때, 연기자와 그래픽의 정확한 합성을 위해, 모션인식 카메라로부터의 연기자 추적 정보를 월드 좌표계로 변환해야 하며, 이것을 수작업으로 하기에는 변환의 정확도가 많이 떨어지고 시간도 많이 소요된다. 본 논문에서는 체크박스 패턴 기반의 스테레오 카메라보정 알고리즘을 사용하여 모션인식카메라와 방송용 카메라간의 상관관계(이동, 회전)를 찾고, 이 값과 월드 좌표계 상의 방송 카메라(하드웨어 센서에 의해서 추적됨)정보(이동, 회전)를 이용하여 임의 위치에 설치한 모션인식 카메라로부터 추적된 연기자 위치정보를 월드 좌표계 상의 위치 값으로 자동 변환시키는 방법을 제안한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.135-137
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• 2013

본 논문은 포인터 레이저를 이용한 3D 스캔방식을 제안한다. 3D 스캔이란 물체의 3차원 정보(x, y, z)를 추정하는 기술이다. 3D 스캔 기술은 과거에서부터 많은 연구가 진행 되었으며 스테레오 카메라, 패턴 인식 등 다양한 방식으로 3파원 정보를 추정 한다. 기존의 방식들은 물체의 표면 정보를 정확하게 스캔하는 장점을 가졌지만, 스캐너의 비용이 비싸고, 그 부피가 크다는 단점 때문에 상용화에 어려움이 많다. 본 논문은 기존 방법보다 부피가 작고 가벼우며 시스템 비용이 적은 포인터 레이저를 이용하여 3차원 정보를 추정하는 방법에 대하여 설명한다. 물체의 깊이 정보(z)에 따른 포인터 레이저의 영상에서의 위치 변화를 통하는 방식으로 3차원 정보 추정을 구현 하였다. 실험을 통하여 포인터 레이저만으로 3차원 정보가 추정 되는 것을 확인한다. 위 방법은 3D 스캐너의 부피가 최소화 되므로 다양한 제품에 부착되어 3D 스캐너의 상용화를 기대한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.895-897
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• 2005

인간 행동 분석은 컴퓨터 비전 및 패턴인식 분야에서 활발하게 연구가 이루어지는 분야이다. 이러한 행동 분석하고 평가하기 위해서는 다양한 환경과 종류의 제스쳐를 포함하고 있는 데이터베이스의 구축이 필수적이다. 본 논문에서는 총 40명의 사람에 대하여 일상생활에서 일어날 수 있는 14개의 정상 제스처, 위급한 상황에서 발생할 수 있는 10개의 비정상 제스처 그리고 30개의 명령형 제스처를 수집한 KU(Korea University) 제스처 데이터베이스를 소개한다. 각각의 제스처는 스테레오 카메라를 통해 얻어진 2차원 제스처 동영상, 3차원 동작 카메라를 통해 얻어진 3차원 모델의 좌표 정보 그리고 2차원 실루엣 동영상을 포함하고 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.133-140
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• 2005

This paper presents a rapid face shape acquisition system. The system is composed of two cameras and one projector. The technique works by projecting a pattern on the object and capturing two images with two cameras. We use a 'one shot' system which provides 3D data acquired by single image per camera. The system is good for rapid data acquisition as our purpose. We use the 'absolutely coded pattern' using the hue and saturation of pattern lines. In this 'absolutely coded pattern' all patterns have absolute identification numbers. We solve the correspondence problem between the two images by using epipolar geometry and absolute identification numbers. In comparison to the 'relatively coded pattern' which uses relative identification numbers, the 'absolutely coded pattern' helps obtain rapid 3D data by one to one point matching on an epipolar line. Because we use two cameras, we obtain two images which have similar hue and saturation. This enables us to have the same absolute identification numbers in both images, and we can use the absolutely coded pattern for solving the correspondence problem. The proposed technique is applied to face data and the total time for shape acquisition is estimated.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.135-140
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• 2012

The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.8
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• pp.597-609
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• 2020

These days, the coaxial rotor system is used for various purposes like UAVs, Mars exploration helicopters, and the next-generation high-speed rotorcraft. A number of research projects on aerodynamic performance of rotor systems, including the coaxial configuration have been made previously. On the contrary, research on rotor blade deformation has been mainly carried out regarding the single rotor system, where such effort has not been enough on the coaxial system. Nonetheless, in case of the coaxial system, blade deformation analysis is much more important because of the complex air flow around the rotors, and that the distance between the two rotors is a key factor affects aerodynamic performance of the entire system. For these reasons, an experimental study on rotor blade deformation of the coaxial system was conducted using the Stereo Pattern Recognition(SPR) technique, one of the state-of-the-art of photogrammetry method. In this research, a small-scale coaxial rotor test stand designed by Korea Aerospace Research Institute(KARI) was used. With the same test stand, performance of the coaxial configuration had been studied before the experimental study on blade deformation, in order to find the relation between performance and blade deformation of the rotor system. Results of the performance test and the deformation study are presented in this article.