• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.619-628
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• 2011

Normally vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment. On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part. In this paper, we describe a development of interactive game contents using pose recognition interface that using 3D human body joint information. Our system was proposed for the purpose that users can control the game contents with body motion without any additional equipment. Poses are recognized comparing current input pose and predefined pose template which is consist of 14 human body joint 3D information. We implement the game contents with the our pose recognition system and make sure about the efficiency of our proposed system. In the future, we will improve the system that can be recognized poses in various environments robustly.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.163-170
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• 2007

In autonomous navigation of a mobile vehicle or a mobile robot, localization calculated from recognizing its environment is most important factor. Generally, we can determine position and pose of a camera equipped mobile vehicle or mobile robot using INS and GPS but, in this case, we must use enough known ground landmark for accurate localization. hi contrast with homography method to calculate position and pose of a camera by only using the relation of two dimensional feature point between two frames, in this paper, we propose a method to calculate the position and the pose of a camera using relation between the location to predict through perspective transform of 3D feature points obtained by overlaying 3D model with previous frame using GPS and INS input and the location of corresponding feature point calculated using KLT tracking method in current frame. For the purpose of the performance evaluation, we use wireless-controlled vehicle mounted CCD camera, GPS and INS, and performed the test to calculate the location and the rotation angle of the camera with the video sequence stream obtained at 15Hz frame rate.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.43-54
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• 2012

This paper presents a new localization technique of an UGV(Unmanned Ground Vehicle) by matching ortho-edge images generated from a DSM (Digital Surface Map) which represents the 3D geometric information of an outdoor navigation environment and 3D range data which is obtained from a LIDAR (Light Detection and Ranging) sensor mounted at the UGV. Recent UGV localization techniques mostly try to combine positioning sensors such as GPS (Global Positioning System), IMU (Inertial Measurement Unit), and LIDAR. Especially, ICP (Iterative Closest Point)-based geometric registration techniques have been developed for UGV localization. However, the ICP-based geometric registration techniques are subject to fail to register 3D range data between LIDAR and DSM because the sensing directions of the two data are too different. In this paper, we introduce and match ortho-edge images between two different sensor data, 3D LIDAR and DSM, for the localization of the UGV. Details of new techniques to generating and matching ortho-edge images between LIDAR and DSM are presented which are followed by experimental results from four different navigation paths. The performance of the proposed technique is compared to a conventional ICP-based technique.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.279-287
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• 2006

This paper proposes a method to detect fall action by using stereo images to recognize emergency situation. It uses 3D information to extract the visual information for learning and testing. It uses HMM(Hidden Markov Model) as a recognition algorithm. The proposed system extracts background images from two camera images. It extracts a moving object from input video sequence by using the difference between input image and background image. After that, it finds the bounding rectangle of the moving object and extracts 3D information by using calibration data of the two cameras. We experimented to the recognition rate of fall action with the variation of rectangle width and height and that of 3D location of the rectangle center point. Experimental results show that the variation of 3D location of the center point achieves the higher recognition rate than the variation of width and height.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.105-112
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• 1999

Image Processing Technique has been used as an efficient method to collect traffic information on the road such as vehicle counts, speed, queues, congestion and incidents. Most of the current methods which have been used to detect vehicles by the image processing are based on point processing, dealing with the local gray level of each pixel in the small window. However, these methods have some drawbacks. Firstly, detection is restricted by image quality. Secondly, they can not deal with occlusion and perspective projection problems, In this research, a new method which possibly deals with occlusion and perspective problems will be proposed. It extracts spatial information such as the position, the relationship of vehicles in 3-dimensional space, as well as vehicle detection in the image. The main algorithm used in this research is based on an extension of the Hough Transform. The Hough Transform which is proposed to estimates parameters of vertices and directed edges analytically on the Hough Space, is a valuable method for the 3-dimensional analysis of static scenes, motion detection and the estimation of viewing parameters.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.157-158
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• 2020

항만용 자율주행 야드트럭운행 환경은 무신호교차로 주행, 낮은 GPS정확도, 악천후상황주행, 이송 컨테이너 위치변경등과 같이 일반 도로의 센서기반의 자율주행차량 운행과 다르게 매우 복잡하다. 이를 위해서는 항만내 특성을 반영한 실시간 위치, 속도 등에 대한 정확한 인식이 중요한 요소이다. 이를 위해서 센서융합과 V2X기반의 복합적인 항만용 실시간 로컬 동적지도 (Local Dynamic Map) 생성 및 V2X기반의 협력측위를 통하여서 기존의 독립적인 자율주행차량의 위치 인식보다 더 개선된 고정밀 위치 인식 정보추출이 필요하다. 본 연구에서는 복합적인 항만용 동적지도 생성관리시스템의 설계 방안 및 협력측위 기술 적용 방안을 제시하고 이를 활용한 항만 구역내 자율주행차량 및 모든 화물 이송장비들의 실시간 위치 인식뿐만 아니라 이동체의 사전 충돌예측 및 비상정지 안전 제어 가능한 V2X 기반의 인텔리젼스 한 3차원 관제시스템 설계 방안을 제시하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.31-40
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• 2003

Most face recognition systems are based on 2D images and applied in many applications. However, it is difficult to recognize a face when the pose varies severely. Therefore, head pose estimation is an inevitable procedure to improve recognition rate when a face is not frontal. In this paper, we propose a novel head pose estimation algorithm for 3D face recognition. Given the 3D range image of an unknown face as an input, we automatically extract facial feature points based on the face curvature. We propose an Error Compensated Singular Value Decomposition (EC-SVD) method based on the extracted facial feature points. We obtain the initial rotation angle based on the SVD method, and perform a refinement procedure to compensate for remained errors. The proposed algorithm is performed by exploiting the extracted facial features in the normaized 3D face space. In addition, we propose a 3D nearest neighbor classifier in order to select face candidates for 3D face recognition. From simulation results, we proved the efficiency and validity of the proposed algorithm.

• Korean Journal of Cognitive Science
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• v.22 no.2
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• pp.103-121
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• 2011

This study investigated how spatial dimension information and dimensional consistency between learning and testing phase would influence the target search performance. The participants learned spatial layouts of Lego blocks shown in either two- (2D) or three-dimension (3D) and were tested with the rotated stimuli ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, or $270^{\circ}$ from the initial view) in consistent or inconsistent dimension. Significantly better performance was observed when initial learning display appeared in 2D than in 3D. Particularly, the participants showed difficulties in flexible usage of spatial information presented in 3D especially if the dimensional information in the testing phase also was 3D and required mental rotation. The present study indicates that spatial map presented in 2D may be more useful than 3D in driving situations in which acquired spatial information from navigating device, such as GPS, and location of driver continuously changes.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.127-136
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• 2012

Many research of hand gesture recognition based on vision system have been conducted which enable user operate various electronic devices more easily. 3D position calculation and meaningful gesture classification from similar gestures should be executed to recognize hand gesture accurately. A simple and cost effective method of 3D position calculation and gesture spotting (a task to recognize meaningful gesture from other similar meaningless gestures) is described in this paper. 3D position is achieved by calculation of two cameras relative position through pan/tilt module and a marker regardless with the placed position. Fuzzy garbage model is proposed to provide a variable reference value to decide whether the user gesture is the command gesture or not. The reference is achieved from fuzzy command gesture model and fuzzy garbage model which returns the score that shows the degree of belonging to command gesture and garbage gesture respectively. Two-stage user adaptation is proposed that off-line (batch) adaptation for inter-personal difference and on-line (incremental) adaptation for intra-difference to enhance the performance. Experiment is conducted for 5 different users. The recognition rate of command (discriminate command gesture) is more than 95% when only one command like meaningless gesture exists and more than 85% when the command is mixed with many other similar gestures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.1923-1932
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• 2008

In this paper, We suggest a method, which extract the 3-Dimension location coordinate of object, stat and coil, using Laser sensor. In order to extract the 3-Dimension location coordinate of object, First, we extract the edge of object. Second, extract the z-axis angle of Laser sensor. Third, extract the 2-Dimension location coordinate of object using edge of object and z-axis of Laser senor. Fourth, discriminate between Slat and Coil. The result of study is expected that the help which is considerable to the automation system development of unmanned transportation equipment will become.