• Journal of KIISE:Computer Systems and Theory
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• v.32 no.8
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• pp.418-425
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• 2005

3D surface reconstruction is to make the original geometry of 3D objects from 2D geometric information. Barequet's algorithm is well known and most widely used in surface reconstruction. It tiles matched regions first, then triangulates clefts using dynamic programming. However it takes considerably long processing time while manipulating complex model. Our method tiles a simple region that does not have branches along minimally distant vertex pairs at once. When there are branches, our method divides contour lines into a simple region and clefts. We propose a fast and simple method that calculates medial axes using a minimum distance in cleft region. Experimental results show that our method can produce accurate models than the previous method within short time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.108-114
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• 2007

This paper presented an image reconstruction method based on the original capsule endoscopy photos yielding a 2-D image for faster diagnosis proposes. The proposed method constructed a 3-D intestine model using the massive images obtained from the capsule endoscope. It merged all images and completed a 3-D model of an intestine. This 3-D model was reformed as a 2-D plane image showing the inner side of the entire intestine. The proposed image composition was evaluated by the 3-D simulator, OpenGL. This approach was demonstrated successfully. A physician can find the location of a disease at a glance because the composite image provided an easy-to-understand view to show the patient's intestine and thereby shorten diagnosis time.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.537-543
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• 2004

In order to create three-dimensional model for human body, a method that reconstructs geometric models from contour lines on cross-section images is commonly used. We can get a set of contour lines by acquiring CT or MR images and segmenting anatomical structures. Previously proposed method divides entire contour line into simply matched regions and clefts. Since long processing time is required for reconstructing cleft regions, its performance might be degraded when manipulating complex data such as cross-sections for human body. In this paper, we propose a fast reconstruction method. It generates a triangle strip with single tiling operation for simple region that does not contain branch structures. If there exist branches in contour lines, it partitions the contour line into several sub-contours by considering the number of vertices and their spatial distribution. We implemented an automatic surface reconstruction system by using our method which reconstructs three-dimensional models for anatomical structures.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.715-717
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• 2003

2차원 의료 영상으로부터 3차원 모델을 재구성 하면 여러 의학 분야에 효과적으로 활용할 수 있다. 컬러 영상이나 MRI의 영상은 표면을 자동으로 식별하기 어렵기 때문에 구역화한 결과로 나오는 외곽선으로부터 표면을 재구성해야한다. 표면 재구성을 위한 기존의 삼각형화 알고리즘은 모델이 복잡할 경우 수행속도가 저하되는 단점이 있다. 본 논문에서는 정합되는 부분과 나머지 부분을 따로 처리하는 기존 방법 대신에, 알맞은 위치에 연결간선들만 결정하여 연결한 후, 그 사이의 정점들을 연결하는 간단한 삼각형화 알고리즘으로 속도를 향상시키는 방법을 제안한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.932-938
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• 2012

Facial expression has its significance in mutual communication. It is the only means to express human's countless inner feelings better than the diverse languages human use. This paper suggests muscle model-based 3D facial expression generation system to produce easy and natural facial expressions. Based on Waters' muscle model, it adds and used necessary muscles to produce natural facial expressions. Also, among the complex elements to produce expressions, it focuses on core, feature elements of a face such as eyebrows, eyes, nose, mouth, and cheeks and uses facial muscles and muscle vectors to do the grouping of facial muscles connected anatomically. By simplifying and reconstructing AU, the basic nuit of facial expression changes, it generates easy and natural facial expressions.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.5-8
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• 2016

키 프레임 추출 기법은 2차원 비오 영상을 3차원으로 재구성하기 위해 꼭 필요한 프레임을 선택하는 방법이다. 본 논문에서는 비디오에서 빠르게 프레임을 검사하며 최적의 키 프레임을 선택하는 기법을 제안한다. 제안하는 기법은 3차원 재구성을 위한 전처리 과정에 초점을 둔 것으로 프레임 간 대응점 비율 검사를 통해 프레임의 도약 강도를 결정하고 기하 모델 추정이 원활한 프레임을 선택한다. 이로부터 3차원 복원 후처리 과정을 통해 최종적인 3차원 점군(point cloud) 데이터를 획득한다. 실험을 통해 다른 기법과 성능을 비교했을 때, 제안하는 기법이 복원 소요 시간도 적게 들고 보다 밀집된 3차원 데이터를 얻을 수 있었다.

• The Journal of Engineering Geology
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• v.31 no.2
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• pp.179-186
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• 2021

Malpasset Dam, located in France, is of great importance in the field of civil and geotechnical engineering as it was the first arch dam that totally collapsed in 1959. A three-dimensional model of the dam was reconstructed using close-range photogrammetry technique. The orientations of foliation developed in the bedrock and the collapse surface were measured. Moreover, both model and measurement results showed high precision. The study result can be used in future studies such as collapse simulation analysis and geotechnical investigations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.37-38
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• 2009

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.12-16
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• 2012

Purpose : In conventional PET image reconstruction, iterative reconstruction methods such as OSEM (Ordered Subsets Expectation Maximization) have now generally replaced traditional analytic methods such as filtered back-projection. This includes improvements in components of the system model geometry, fully 3D scatter and low noise randoms estimates. SharpIR algorithm is to improve PET image contrast to noise by incorporating information about the PET detector response into the 3D iterative reconstruction algorithm. The aim of this study is evaluation of SharpIR reconstruction method in PET/CT. Materials and Methods: For the measurement of detector response for the spatial resolution, a capillary tube was filled with FDG and scanned at varying distances from the iso-center (5, 10, 15, 20 cm). To measure image quality for contrast recovery, the NEMA IEC body phantom (Data Spectrum Corporation, Hillsborough, NC) with diameters of 1, 13, 17 and 22 for simulating hot and 28 and 37 mm for simulating cold lesions. A solution of 5.4 kBq/mL of $^{18}F$-FDG in water was used as a radioactive background obtaining a lesion of background ratio of 4.0. Images were reconstructed with VUE point HD and VUE point HD using SharpIR reconstruction algorithm. For the clinical evaluation, a whole body FDG scan acquired and to demonstrate contrast recovery, ROIs were drawn on a metabolic hot spot and also on a uniform region of the liver. Images were reconstructed with function of varying iteration number (1~10). Results: The result of increases axial distance from iso-center, full width at half maximum (FWHM) is also increasing in VUE point HD reconstruction image. Even showed an increasing distances constant FWHM. VUE point HD with SharpIR than VUE point HD showed improves contrast recovery in phantom and clinical study. Conclusion: By incorporating more information about the detector system response, the SharpIR algorithm improves the accuracy of underlying model used in VUE point HD. SharpIR algorithm improve spatial resolution for a line source in air, and improves contrast recovery at equivalent noise levels in phantoms and clinical studies. Therefore, SharpIR algorithm can be applied as through a longitudinal study will be useful in clinical.