• Journal of the Korea Computer Graphics Society
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• 제21권5호
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• pp.37-44
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• 2015

This paper presents a novel 3D model representation, called hybrid model representation, to overcome existing 3D volume-based indoor scene reconstruction mechanism. In indoor 3D scene reconstruction, volume-based model representation can reconstruct detailed 3D model for the narrow scene. However it cannot reconstruct large-scale indoor scene due to its memory consumption. This paper presents a memory efficient plane-hash model representation to enlarge the scalability of the indoor scene reconstruction. Also, the proposed method uses plane-hash model representation to reconstruct large, structural planar objects, and at the same time it uses volume-based model representation to recover small detailed region. Proposed method can be implemented in GPU to accelerate the computation and reconstruct the indoor scene in real-time.

• Journal of KIISE:Software and Applications
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• 제31권11호
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• pp.1543-1550
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• 2004

Modeling from images is a cost-effective means of obtaining 3D geometric models. These models can be effectively constructed from classical Structure from Motion algorithm. However, it's too difficult to reconstruct whole scenes using SFM method since general sites contain a very complex shapes and brilliant colours. To overcome this difficulty, the current paper proposes a new reconstruction method based on a moving Planar mirror. We devise the mirror posture instead of scene itself as a cue for reconstructing the geometry That implies that the geometric cues are inserted into the scene by compulsion. With this method, we can obtain the geometric details regardless of the scene complexity. For this purpose, we first capture image sequences through the moving mirror containing the interested scene, and then calibrate the camera through the mirror's posture. Since the calibration results are still inaccurate due to the detection error, the camera pose is revised using frame-correspondence of the comer points that are easily obtained using the initial camera posture. Finally, 3D information is computed from a set of calibrated image sequences. We validate our approach with a set of experiments on some complex objects.

• The Journal of the Petrological Society of Korea
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• 제23권2호
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• pp.139-144
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• 2014

A series of the planar cathodoluminescence (CL) and backscattered-electron (BSE) images of magmatic zircon from the Paleozoic Yeongdeok pluton in the southeastern Korean Peninsula were taken using a scanning electron microscope for a 3D reconstruction of internal zonation of zircon. Seven zircon crystals mounted in epoxy were serially polished with average $3{\mu}m$ thickness to their disappearance. Their 3D reconstruction of zonation was performed using the Volume Viewer function in the ImageJ software. The 3D oscillatory zoning pattern of zircon was apparently shown in all the analyzed crystals. This method can further be applied to zircon crystals of multiple growth histories as well as other geological materials.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2006년도 학술대회 1부
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• pp.486-492
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• 2006

본 논문에서는 비디오에서의 특징점 추적을 통해 얻은 2D 좌표를 이용한 3D 구조를 추정하는 방법과 네 점 이상의 공통점을 이용한 융합 방법을 제안한다. 영상의 각 프레임에서 공통되는 특징점을 이용하여 형상을 추정한다. 영상의 각 프레임에 대한 특징점의 추적은 Lucas-Kanade 방법을 사용하였다. 3D 좌표 추정 방법으로 개선된 직교분해기법을 사용하였다. 개선된 직교분해기법에서는 3D 좌표를 복원함과 동시에 카메라의 위치와 방향을 계산할 수 있다. 복원된 부분 데이터들은 전체를 이루는 일부분이므로, 융합을 통해 완성된 모습을 만들 수 있다. 복원된 부분 데이터들의 서로 다른 좌표계를 기준 좌표계로 변환함으로써 융합할 수 있다. 융합은 카메라의 모션에 해당하는 카메라의 위치와 방향에 의존된다. 융합 과정은 모두 선형으로 평균 0.5초 이하의 수행 속도를 보이며 융합의 오차는 평균 0.1cm 이하의 오차를 보였다.

• Proceedings of the Korea Contents Association Conference
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• 한국콘텐츠학회 2008년도 춘계 종합학술대회 논문집
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• pp.15-18
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• 2008

This paper proposes a method to reconstruct the 3-D face using structured light image. First of all, we suppose that each sight vector of a projector and camera are parallel. We project the structured light in the shape of lattice on the background to acquire the reference-structured light image. This image is used to calibrate the projector and camera. Since then, we acquire the face-structured light image which is projected the same structured light on the face. These two structured light images are used to reconstruct the 3-D face through the variation which is measured from the positional difference of feature vectors. In our experiment result, we could reconstruct the 3-D face image as recognize through these simple devices.

• The KIPS Transactions:PartB
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• 제17B권3호
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• pp.215-226
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• 2010

The structured-light 3D reconstruction technique uses a coded-pattern to find correspondences between the camera image and the projector image. To calculate the 3D coordinates of the correspondences, it is necessary to calibrate the camera and the projector. In addition, the calibration results affect the accuracy of the 3D reconstruction. Conventional camera-projector calibration techniques commonly require either expensive hardware rigs or complex algorithm. In this paper, we propose an easy camera-projector calibration technique. The proposed technique does not need any hardware rig or complex algorithm. Thus it will enhance the efficiency of structured-light 3D reconstruction. We present two camera-projector systems to show the calibration results. Error analysis on the two systems are done based on the projection error of the camera and the projector, and 3D reconstruction of world reference points.

• Electronics and Telecommunications Trends
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• 제27권3호
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• pp.12-21
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• 2012

최근 3DTV, 입체 모니터, 입체 노트북 등이 출시되고, 3D 영화, 게임 등 3D 관련 산업이 성장하면서 관련 콘텐츠의 요구사항이 증가하고 있다. 특히, 3D 콘텐츠의 주요 요소 중 하나인 인체는 전통적으로 고가의 3D 스캐너를 이용해 모델링하는 방식을 주로 사용해 왔다. 하지만 근래에는 광학 기술 및 컴퓨팅 성능의 향상으로 구조광과 같은 능동 센서나 카메라로부터 획득한 영상을 기반으로 3D 인체 외형을 복원하는 연구가 각광을 받고 있다. 이런 추세에 발맞춰 본고에서는 인체 중에서도 사용자의 민감도가 높은 얼굴의 3D 복원 기술 및 연구 동향을 살펴보고, 다양한 응용을 목적으로 ETRI에서 개발 중인 3D 얼굴 복원 기술을 소개하고자 한다.

• Journal of Korea Multimedia Society
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• 제12권9호
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• pp.1217-1232
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• 2009

In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

• Proceedings of the Korea Contents Association Conference
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.248-251
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• 2007

In this paper, we are propose a method to estimate the 2-D mesh from structured light image for reconstruction of 3-D face image. To acquire the structured light image, we are project structured light on the face using the projector. we are extract the projected cross points from the acquire image. The 2-D mesh image is extracted from the position and angle of cross points. In the extraction processing, the error was fixed to extract the correct 2-D mesh.

• The KIPS Transactions:PartB
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• 제12B권5호
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• pp.567-576
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• 2005

This paper proposes an image-based modeling method which recovers 3D models using projected line segments in multiple images. Using the method, a user obtains accurate 3D model data via several steps of simple manual works. The embedded nonlinear minimization technique in the model parameter estimation stage is based on the distances between the user provided image line segments and the projected line segments of primitives. We define an error using a finite line segment and thus increase accuracy in the model parameter estimation. The error is defined as the sum of differences between the observed image line segments provided by the user and the predicted image line segments which are computed using the current model parameters and camera parameters. The method is robust in a sense that it recovers 3D structures even from partially occluded objects and it does not be seriously affected by small measurement errors in the reconstruction process. This paper also describesexperimental results from real images and difficulties and tricks that are found while implementing the image-based modeler.