• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.115-122
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• 2017

As the era of the fourth industrial revolution began, augmented reality showed infinite possibilities throughout society. However, current augmented reality systems such as head-mount display and hand-held display systems suffer from various problems such as weariness and nausea, and thus space-augmented reality, which is a projector-based augmented reality technology, is attracting attention. Spacial augmented reality requires precise tracking of dynamic objects to project virtual images in order to increase realism of augmented reality and induce user 's immersion. The infrared sensor-based precision tracking algorithm developed in this paper demonstrates very robust tracking performance with an average error rate of less than 1.5% and technically opens the way towards advanced augmented reality technologies such as tracking for arbitrary objects, and Socially, by easy-to-use tracking algorithms for non-specialists, it allows designers, students, and children to easily create and enjoy their own augmented reality content.

• Journal of the Korea Computer Graphics Society
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• v.16 no.2
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• pp.29-37
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• 2010

In this paper, we present a novel deformation method for alleviating the asymmetry of a scanned 3D face considering facial features. To handle detailed areas of the face, we developed a new local 3D shape descriptor based on facial features and surface curvatures. Our shape descriptor can improve the accuracy when deforming a 3D face toward a symmetric configuration, because it provides accurate point pairing with respect to the plane of symmetry. In addition, we use point-based representation over all stages of symmetrization, which makes it much easier to support discrete processes. Finally, we performed a statistical analysis to assess subjects' preference for the symmetrized faces by our approach.

• Journal of the Korea Computer Graphics Society
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• v.27 no.4
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• pp.1-9
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• 2021

Segmenting the compartments of neurons, such as axons, dendrites, and cell bodies, is helpful in the analysis of neurological phenomena. Recently, there have been several studies to segment the compartments through deep learning. However, this approach has the potential to include errors in the results due to noise in data and differences between training data and actual data. Therefore, in order to use these for actual analysis, it is essential to proofread the results. The proofreading process requires a lot of effort and time because an expert must perform it manually. We propose an interactive neuron structure proofreading method that can more easily correct errors in the segmentation results of a deep learning. This method proofread the neuron structure based on the characteristics of the neuron with structural consistency, so that a high-accuracy proofreading result can be obtained with less interaction.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.1-9
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• 2019

The image obtained from systems such as autonomous driving cars or fire-fighting robots often suffer from several degradation such as noise, motion blur, and compression artifact due to multiple factor. It is difficult to apply image recognition to these degraded images, then the image restoration is essential. However, these systems cannot recognize what kind of degradation and thus there are difficulty restoring the images. In this paper, we propose the deep neural network, which restore natural images from images degraded in several ways such as noise, blur and JPEG compression in situations where the distortion applied to images is not recognized. We adopt the channel attention modules and skip connections in the proposed method, which makes the network focus on valuable information to image restoration. The proposed method is simpler to train than other methods, and experimental results show that the proposed method outperforms existing state-of-the-art methods.

• Journal of the Korea Computer Graphics Society
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• v.24 no.5
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• pp.11-19
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• 2018

In this paper, we propose an algorithm for improving the accuracy and rate of convergence when two point clouds with noise and a low overlapping area are registered to each other. We make the most use of the geometric information of the underlying geometry of the point clouds with noise for better accuracy. We select a reasonable region from the noisy point cloud for registration and combine a modified acceleration algorithm to improve its speed. The conventional accuracy improvement method was not possible in a lot of noise, this paper resolves the problem by selecting the reasonable region for the registration. And this paper applies acceleration algorithm for a clone to low overlap point cloud pair. A simple algorithm is added to the conventional method, which leads to 3 or 4 times faster speed. In conclusion, this algorithm was developed to improve both the speed and accuracy of point cloud registration in noisy and low overlap case.

• Journal of the Korea Computer Graphics Society
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• v.25 no.2
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• pp.31-41
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• 2019

Extended Reality (XR), such as virtual and augmented reality, has huge potential for immersive data visualization and analysis. In XR, users can interact with data and other users realistically by navigating the shared virtual space, allowing for more intuitive data analysis. However, creating a visualization in XR also poses a challenge because complicated, low-level programming is required, which hinders broad adaptation in visual analytics. This paper proposes an interactive visualization authoring tool based on hand gesture for immersive data visualization-Gadget Arms. The proposed system provides a novel user interaction to create and place visualization in the 3D virtual world. This simple, but intuitive, user interaction enables user designs the entire visualization space in the XR without using a host computer and low-level programming. Our user study also confirmed that the proposed user interaction significantly improves the usability of the visualization authoring tool.

• Journal of the Korea Computer Graphics Society
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• v.29 no.1
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• pp.13-22
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• 2023

In this paper, we present a method for estimating full 3D shapes from given 2D silhouette images of human bodies. Because the silhouette only consists of the partial information on the true shape, it is an ill-posed problem. To address the problem, we use the statistical human shape space obtained from the existing large 3D human shape database. The method consists of three steps. First, we extract the boundary pixels and their appropriate normal vectors from the input silhouette images. Then, we initialize the correspondences of each pixel to the vertex of the statistically-deformable 3D human model. Finally, we numerically optimize the parameters of the statistical model to fit best to the given silhouettes. The viability and the robustness of the method is demonstrated with various experiments.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.453-456
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• 1998

컴퓨터 그래픽스 기술의 발전과 더불어 인체의 움직임을 사실적으로 구현하기 위한 연구가 활발하게 진행되고 있다. 본 논문에서는 인체의 동력학적 특성을 고려한 실시간 애니메이션이 가능하도록 인체를 모델링하였다. 인체의 동력학적 특성을 해석하기 위하여 인체를 16 자유도를 갖는 강체(rigid body)로 가정하였으며 Branch 형태의 복잡한 기구학적 형상을 가진 인체를 5개의 단순한 형태의 기구학적 연결체로 분할 하여 모델링을 수행하였다. 이러한 동력학 모델은 단순히 기구학 만을 이용하는 경우보다 사실적이면서도 실시간으로 애니메이션이 가능하다. 이와 같이 동력학적 모델을 사용하여 애니메이션을 수행할 경우 부가적인 장비를 사용하지 않고도 다양한 형태의 인간 움직임을 사실적으로 모사할 수 있다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.326-329
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• 2003

영상이나 이미지로부터 3차원 정보를 복원해내기 위한 기술은 컴퓨터 비젼과 그래픽스 분야에서 많은 연구의 대상이 되어 왔다. 본 연구에서는 연속적으로 획득된 여러 장의 이미지로부터 특징점을 추출한 후 그 점들로부터 프로젝티브 복원을 하고 카메라 파라메터를 계산하여 유클리디언 공간으로 변환시켜 3차원 데이터를 계산하는 방법을 구현하였다. 계산된 3차원 데이터와 가장 적합한 폴리곤을 선택하고 텍스쳐 매핑을 하는 방법을 결합하여 사실적인 3차원 모델을 생성할 수 있었다.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.579-584
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• 2001

컴퓨터 그래픽스 기술을 이용한 응용분야가 증가함에 따라 물체의 사실적인 모델에 대한 요구가 증가되고 있다. 모델링 시간이 많이 필요한 기존의 3차원 모델링 툴 외에 최근에 사용자의 스케치에 기반한 모델링 방법과 영상기반 모델링, 3차원 스캐너가 발표되었지만, 정확성이 떨어지거나 고가의 장비를 필요로 하는 단점이 있다. 본 논문에서는 정육면체 프레임과 광평면(light plane) 프로젝터, 카메라를 이용한 물체의 3차원 구조 복원 시스템을 제안하고, 실험을 통하여 모델링의 정확도를 분석한다.