• 제어로봇시스템학회논문지
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• 제22권12호
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• pp.1061-1067
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• 2016

Position of the vehicle for driving is essential to autonomous navigation. However, there appears GPS position error due to multipath which is occurred by tall buildings in downtown area. In this paper, GPS position error is corrected by using camera sensor and highly accurate map made with 3D-Lidar. Input image through inverse perspective mapping is converted into top-view image, and it works out map matching with the map which has intensity of 3D-Lidar. Performance comparison was conducted between this method and traditional way which does map matching with input image after conversion of map to pinhole camera image. As a result, longitudinal error declined 49% and complexity declined 90%.

• 한국컴퓨터그래픽스학회논문지
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• 제3권1호
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• pp.23-28
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• 1997

본 논문은 range map과 texture map이 포함된 range image를 삼각형 메쉬로 된 3차원 형상으로 복원하고, 이 삼각형 메쉬를 기하학적 축소 알고리즘을 적용하여 간략화하는 방법에 대하여 기술한다. 그리고 이 논문에는 복원된 3차원 모델에 texture mapping이 가능하고 간략한 정도를 사용자가 쉽게 결정할 수 있으며, 실시간 multiple level-of-detail에 적용 가능한 빠른 속도의 간략화 방법을 제시한다. 구현한 방법을 국보급 문화재를 스캐닝한 실험 데이터에 적용하여 그 유효성을 입증한다.

• 전자통신동향분석
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• 제35권5호
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• pp.112-122
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• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• 한국멀티미디어학회논문지
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• 제13권12호
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• pp.1855-1862
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• 2010

In virtual reality, there are increasing qualitative development in service technologies for realtime interaction system development, 3- dimensional contents, 3D TV and augment reality services. These services experience difficulties to generate depth value that is essential to recover 3D space to form solidity on existing contents. Hence, research for the generation of effective depth-map using 2D is necessary. This thesis will describe a shortcoming of an existing depth-map generation for the recovery of 3D space using 2D image and will propose an enhanced depth-map generation algorithm that complements a shortcoming of existing algorithms and utilizes the definition of depth direction based on the vanishing point within image.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1887-1890
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm using the stereo image. Given a pair of stereo image, we automatically extract several important facial feature points using the disparity map, the gabor filter and the canny edge detector. To detect the facial feature region , we propose a region dividing method using the disparity map. On the indoor head & shoulder stereo image, a face region has a larger disparity than a background. So we separate a face region from a background by a divergence of disparity. To estimate 3D head pose, we propose a 2D-3D Error Compensated-SVD (EC-SVD) algorithm. We estimate the 3D coordinates of the facial features using the correspondence of a stereo image. We can estimate the head pose of an input image using Error Compensated-SVD (EC-SVD) method. Experimental results show that the proposed method is capable of estimating pose accurately.

• 한국컴퓨터정보학회논문지
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• 제11권2호
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• pp.177-186
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• 2006

이 논문은 입력 영상에 대해 기존의 영상기반 렌더링 기법을 적용하고 가상공간지도라는 개념을 도입하여 사실적인 3차원 가상공간을 구축할 수 있는 효율적인 저작도구 개발에 대한 연구를 기술하고 있다. TIP 같은 기존의 기법들은 단일 영상을 사용하여 작은 3D가상공간을 구축하는 반면 여기서 제안하는 저작도구는 복수의 영상을 사용하여 광범위한 가상공간을 구축한다. 이 저작도구는 입력영상 각각에 대해 작은 3차원 가상공간을 구축하고 먼저 정의된 가상공간지도를 사용하여 이 독립적인 3D가상공간을 서로 연결하여 광범위한 3D가상공간을 구축할 수 있게 설계되었다. 가상공간지도는 세 가지 구성요소와 세 가지 방향으로 구성되어있다. 세 가지 구성요소는 특정 공간, 연결점 및 통로이고, 세 가지 방향은 정방향, 역방향 및 양방향이다. 가상공간지도는 가상공간의 연결구조, 네비게이션 정보 등 다양한 정보를 가지고 있다. 또한 이 저작도구는 사용자가 광범위한 3차원 가상공간을 쉽게 구축할 수 있게끔 사용자 인터페이스를 제공하고 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.28-30
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• 2009

This paper describes a 3-DTIP(3-D Tour Into Picture) using depth map for a Korean classical painting being composed of persons and landscape. Unlike conventional TIP methods providing 2-D image or video, our proposed TIP can provide users with 3-D stereoscopic contents. Navigating inside a picture provides more realistic and immersive perception. The method firstly makes depth map. Input data consists of foreground object, background image, depth map, foreground mask. Firstly we separate foreground object and background, make each of their depth map. Background is decomposed into polygons and assigned depth value to each vertexes. Then a polygon is decomposed into many triangles. Gouraud shading is used to make a final depth map. Navigating into a picture uses OpenGL library. Our proposed method was tested on "Danopungjun" and "Muyigido" that are famous paintings made in Chosun Dynasty. The stereoscopic video was proved to deliver new 3-D perception better than 2-D video.

• 방송공학회논문지
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• 제16권6호
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• pp.916-926
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• 2011

3D 영화 콘텐츠처럼 고해상도로 만들어진 입체영상은 저해상도 영상에서는 동일한 3D 깊이감을 느낄 수가 없다는 단점이 있다. 본 논문에서는 공간적 복잡도을 이용하여 깊이맵을 변환하여 입체감을 개선할 수 있는 방법을 제안한다. 제안 방법에서는 깊이맵의 히스토그램을 분석한 후에, 깊이맵을 다수의 깊이평면으로 분할한 다음에 깊이 평면을 변환한다. 마지막으로 변환된 깊이평면을 통합하여 최종 깊이맵을 생성한다. 주관적 평가 실험에서는 입체감 개선 및 이에 따라 발생하는 시각적 피로도를 검증하였다. 실험에서는 입체감의 개선이 증명되었으며, 영상 해상도가 낮아져도, 입체감은 유지되는 것을 보여주었다. 또한 얻어진 입체영상의 시각적 피로도 검증을 통해서 생성된 입체영상은 피로도가 증가하지 않는 것을 보여주었다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2010년도 하계학술대회
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• pp.241-243
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• 2010

Previous approaches to the 2D to 3D conversion problem require heavy computation or considerable amount of user input. In this paper, we propose a rather simple method in estimating the depth map from a single image using a monocular depth cue: haze. Using the haze imaging model, we obtain the distance information and estimate a reliable depth map from a single scenery image. Using the depth map, we also suggest an algorithm that converts the single image to 3D stereoscopic images. We determine a disparity value for each pixel from the original 'left' image and generate a corresponding 'right' image. Results show that the algorithm gives well refined depth maps despite the simplicity of the approach.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.123.1-123
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• 2001

For Autonomous navigation of the mobile robots, the robots' capability to recognize 3D environment is necessary. In this paper, an on-line 3D map building method for autonomous mobile robots is proposed. To get range data on the environment, we use an sensor system which is composed of a structured light and a CCD camera based on optimal triangulation. The structured laser is projected as a horizontal strip on the scene. The sensor system can rotate $\pm$ $30{\Circ}$ with a goniometer. Scanning the system, we get the laser strip image for the environments and update planes composing the environment by some image processing steps. From the laser strip on the captured image, we find a center point of each column, and make line segments through blobbing these center poings. Then, the planes of the environments are updated. These steps are done on-line in scanning phase. With the proposed method, we can efficiently get a 3D map about the structured environment.