• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.448-450
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• 2012

본 논문에서는 Kinect 방식의 RGB-D 영상센서를 사용하여, 깊이(Depth) 영상으로부터 3차원 객체의 기하정보를 표현하는 표면 정규 벡터(Surface Normal Vector)를 추출하고, 그 결과를 영상화하는 방법을 제안하며, 제안된 방법으로 생성된 영상으로부터 깊이 영상의 특징점 및 특징 기술자를 추출하여 3차원 객체 인식 성능을 향상시키는 방법을 제안한다. 또한 생성된 RGB-D 특징 기술자들을 객체 단위로 구분 가능한 코드북(CodeBook) 학습을 통한 인식방법을 제안하여 객체의 인식 성능을 높이는 방법을 제안한다. 제안하는 RGB-D 기반의 특징 추출 및 학습 방법은 텍스쳐 유무, 카메라 회전 및 이동 변화 등의 환경변화에 강건함을 실험적으로 증명하였으며, 이 방법은 Kinect 방식의 RGB-D 영상을 사용하는 3차원 객체/공간 인식 및 추적, 혹은 이를 응용하는 증강현실 시스템에 적용하여 사용될 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.517-521
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• 2000

본 논문에서는 영상 처리 방법을 이용하여 주어진 객체의 실세계 좌표를 나타내는 특징점을 인식하는 한 방법을 제안한다. 제안된 방법에서는 육면체 형상의 객체를 대상으로 하며, 이러한 객체 영상의 주요한 특징점은 육면체를 결정짓는 꼭지점들로 이루어진다. 제안된 방법은 CCD 카메라로부터 영상을 획득하는 영상 획득 모듈, 획득된 영상에 대하여 관심 영역을 찾는 영상 분할 모듈, 분할된 관심 영역에 대하여 sobel operator등을 이용하여 경계 정보를 검출하는 영상 처리 모듈, 그리고 세선화, line fitting과정을 통하여 직선 벡터들을 검출한 후에 객체의 주요한 특징점을 인식하는 모듈로 구성된다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.53-62
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• 2011

In this paper, high-tech IT Convergence, to the development of complex technology, special technology, video object recognition technology was considered only as a smart - phone technology with the development of personal portable terminal has been developed crossroads. Technology-based detection of 3D face recognition technology that recognizes objects detected through the intelligent video recognition technology has been evolving technologies based on image recognition, face detection technology with through the development speed is booming. In this paper, based on human face recognition technology to detect the object recognition image processing technology is applied through the face recognition technology applied to the IP camera is the party of the mouth, and allowed the ability to identify and apply the human face recognition, measurement techniques applied research is suggested. Study plan: 1) face model based face tracking technology was developed and applied 2) algorithm developed by PC-based measurement of human perception through the CPU load in the face value of their basic parameters can be tracked, and 3) bilateral distance and the angle of gaze can be tracked in real time, proved effective.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1897-1903
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• 2011

This paper discusses a 2D/3D conversion of images using technologies like object extraction and depth-map creation. The general procedure for converting 2D images into a 3D image is extracting objects from 2D image, recognizing the distance of each points, generating the 3D image and correcting the image to generate with less noise. This paper proposes modified new methods creating a depth-map from 2D image and recognizing the distance of objects in it. Depth-map information which determines the distance of objects is the key data creating a 3D image from 2D images. To get more accurate depth-map data, noise filtering is applied to the optical flow. With the proposed method, better depth-map information is calculated and better 3D image is constructed.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• 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 the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.637-644
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• 2021

In general, in the fields of computer vision, robotics, and augmented reality, the importance of 3D space and 3D object detection and recognition technology has emerged. In particular, since it is possible to acquire RGB images and depth images in real time through an image sensor using Microsoft Kinect method, many changes have been made to object detection, tracking and recognition studies. In this paper, we propose a method to improve the quality of 3D reconstructed images by processing images acquired through a depth-based (RGB-Depth) camera on a multi-view camera system. In this paper, a method of removing noise outside an object by applying a mask acquired from a color image and a method of applying a combined filtering operation to obtain the difference in depth information between pixels inside the object is proposed. Through each experiment result, it was confirmed that the proposed method can effectively remove noise and improve the quality of 3D reconstructed image.

• Journal of Digital Contents Society
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• v.11 no.2
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• pp.243-251
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• 2010

In this paper, 2 devices through the input image are projected onto the output video device to extract 3D information of real objects and they are located in virtual space. All 3D objects for each inter-object interaction information and location information makes the validation process by recognizing conflict. The proposed extract 3D information of real objects and collision handling inter-object interaction in the most basic issues in augmented reality, because more than anything is a matter to be prescriptive. Therefore, the proposed system to solve this problem exists in virtual space, all objects of the user by validating the conflict between realism and immersion to show that aims to increase.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.117-123
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• 2016

A hand-gesture interface to manipulate a 3D object of augmented reality is implemented by recognizing the user hand-gesture in this paper. Proposed method extracts the hand region from real image, and creates augmented object by hand marker recognized user hand-gesture. Also, 3D object manipulation corresponding to user hand-gesture is performed by analyzing a hand region ratio, a numbet of finger and a variation ratio of hand region center. In order to evaluate the performance of the our proposed method, after making a 3D object by using the OpenGL library, all processing tasks are implemented by using the Intel OpenCV library and C++ language. As a result, the proposed method showed the average 90% recognition ratio by the user command-modes successfully.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.1006-1011
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• 2007

Active Appearance Models은 객체의 모델링에 널리 사용되며, 특히 얼굴 모델은 얼굴 추적, 포즈 인식, 표정 인식, 그리고 얼굴 인식에 널리 사용되고 있다. 최초의 AAM은 Shape과 Appearance가 하나의 계수에 의해서 만들어 지는 Combined AAM이였고, 이후 Shape과 Appearance의 계수가 분리된 Independent AAM과 3D를 표현할 수 있는 Combined 2D+3D AAM이 개발 되었다. 비록 Combined 2D+3D AAM이 3D를 표현 할 수 있을지라도 이들은 공통적으로 2D 영상을 사용하여 모델을 생산한다. 본 논문에서 우리는 stereo-camera based 3D face capturing device를 통해 획득한 3D 데이터를 기반으로 하는 3D AAM을 제안한다. 우리의 3D AAM은 3D정보를 이용해 모델을 생산하므로 기존의 AAM보다 정확한 3D표현이 가능하고 Alignment Algorithm으로 Inverse Compositional Image Alignment(ICIA)를 사용하여 빠르게 Model Instance를 생산할 수 있다. 우리는 3D AAM을 평가하기 위해 stereo-camera based 3D face capturing device로 촬영해 수집한 한국인 얼굴 데이터베이스[9]로 얼굴인식을 수행하였다.