• Journal of Ocean Engineering and Technology
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• v.35 no.3
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• pp.183-190
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• 2021

Tomographic particle image velocimetry (PIV) is a widely used method that measures a three-dimensional (3D) flow field by reconstructing camera images into voxel images. In 3D measurements, the setting and calibration of the camera's mapping function significantly impact the obtained results. In this study, a camera self-calibration technique is applied to tomographic PIV to reduce the occurrence of errors arising from such functions. The measured 3D particles are superimposed on the image to create a disparity map. Camera self-calibration is performed by reflecting the error of the disparity map to the center value of the particles. Vortex ring synthetic images are generated and the developed algorithm is applied. The optimal result is obtained by applying self-calibration once when the center error is less than 1 pixel and by applying self-calibration 2-3 times when it was more than 1 pixel; the maximum recovery ratio is 96%. Further self-correlation did not improve the results. The algorithm is evaluated by performing an actual rotational flow experiment, and the optimal result was obtained when self-calibration was applied once, as shown in the virtual image result. Therefore, the developed algorithm is expected to be utilized for the performance improvement of 3D flow measurements.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.171-174
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• 2003

인간 시각이 감지하는 영상정보는 깊이정보가 있는 3차원형태의 정보이다. 이러한 영상정보를 획득하기 위해 2차원의 스테레오영상으로부터 3차원정보를 추출하는 방법이 연구되어왔다. 본 논문에서는 웨이블릿(wavelet) 영역에서의 영역기반 스테레오 매칭(stereo matching)을 통하여 3차원정보를 추출하고 복원하는 것을 제안한다.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.359-366
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• 2003

Although the reuse of the cached data for scrolling the map reduces the amount of passed data between client and server, it needs the conversions of data coordinates, selective deletion of objects, cache compaction and object structuring step in the clients. The conversion is a time- intensive operation due to limited resources of mobile phones such as low computing power, small memory. Therefore, in order to control the map efficiently in the vector map service based mobile phones, it is necessary to study the methods which reuse cached objects for reducing wireless network bandwidth and overwhelming the limited resources of mobile phones as well. This paper proposes the methods of reusing pre-received spatial objects for map control in the mobile vector map service system based on client-server architecture. The experiments conducted on the Web GIS systems with real data show that the proposed method is appropriate to map services for mobile phone. We also analyze the advantages and drawbacks between the reuse of cached data and transmission of raw data respectively.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.471-482
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• 2006

In this paper, we propose a new scheme to generate multi-view images utilizing depth map decomposition and adaptive edge smoothing. After carrying out smooth filtering based on an adaptive window size to regions of edges in the depth map, we decompose the smoothed depth map into four types of images: regular mesh, object boundary, feature point, and number-of-layer images. Then, we generate 3-D scenes from the decomposed images using a 3-D mesh triangulation technique. Finally, we extract multi-view images from the reconstructed 3-D scenes by changing the position of a virtual camera in the 3-D space. Experimental results show that our scheme generates multi-view images successfully by minimizing a rubber-sheet problem using edge smoothing, and renders consecutive 3-D scenes in real time through information decomposition of depth maps. In addition, the proposed scheme can be used for 3-D applications that need the depth information, such as depth keying, since we can preserve the depth data unlike the previous unsymmetric filtering method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.161-168
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• 2010

This study aims to propose a method that shall rapidly acquire 3D information of the fast and frequently changing city areas by using the images taken by the UAV photogrammetric method, and to develop the process of the acquired data. For this study's proposed UAV photogrammetric method, low-cost UAV and non-metric digital camera were used. The elements of interior orientation were acquired through camera calibration. The artificial 3D model of the artificial structures was constructed using the image data photographed at the target area and the results of the ground control point survey. The digital surface model was created for areas that were changed due to a number of civil works. This study also analyzes the proposed method's application possibility by comparing a 1/1,000 scale digital map and the results of the ground control point survey. Through the above studies, the possibilities of constructing a 3D virtual city model renewal of 3D GIS database, abstraction of changed information in geographic features and on-demand updating of the digital map were suggested.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.1 s.39
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• pp.67-73
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• 2007

Recently, three-dimensional (3D) GI (Geospatial Information) using LiDAR system has been used various fields such as the production of digital map, the modeling of 3D building and urban area, and analysis of communication network and environmental effect. In this study, the production cost of digital map by aerial LiDAR surveying were compared with the cost by aerial photograph surveying for analysis of economical efficiency. It is expected that the results of this study will be used base data for production, update, revision of digital map and curtail effect of national budget.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1155-1163
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• 2011

In this paper, we propose a new pre-processing algorithm applied to depth map to improve the coding efficiency. Now, 3DV/FTV group in the MPEG is working for standard of 3DVC(3D video coding), but compression method for depth map images are not confirmed yet. In the proposed algorithm, after dividing the histogram distribution of a given depth map by EM clustering method based on GMM, we classify the depth map into several layered images. Then, we apply different mean shift filter to each classified image according to the existence of background or foreground in it. In other words, we try to maximize the coding efficiency while keeping the boundary of each object and taking average operation toward inner field of the boundary. The experiments are performed with many test images and the results show that the proposed algorithm achieves bits reduction of 19% ~ 20% and computation time is also reduced.

• Communications of the Korean Mathematical Society
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• v.34 no.3
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• pp.951-965
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• 2019

Let $f:X{\rightarrow}X$ be a continuous map on a compact metric space (X, d) and for an arbitrary $x{\in}X$, $${\mathcal{SC}}_d(x,f):=\{y{\mid}x{\text{ can be strong }}d-{\text{chain to }}y\}$$. We give an example to show that ${\mathcal{SC}}_d(x,f)$ is dependent on the metric d on X but it is a closed and f-invariant set. We prove that if ${\mathcal{SC}}_d(x,f){\supseteq}{\Omega}(f)$ or f has the asymptotic-average shadowing property, then ${\mathcal{SC}}_d(x,f)=X$. Also, we show that if f has the shadowing property, then ${\lim}\;{\sup}_{n{\in}{\mathbb{N}}}\{f^n\}={\mathcal{SC}}_d(f)$ where ${\mathcal{SC}}_d(f)=\{(x,y){\mid}y{\in}{\mathcal{SC}}_d(x,f)\}$. For each $n{\in}{\mathbb{N}}$, we give an example in which ${\mathcal{SCR}}_d(f^n){\neq}{\mathcal{SCR}}_d(f)$. In spite of it, we prove that if $f^{-1}:(X,d){\rightarrow}(X,d)$ is an equicontinuous map, then ${\mathcal{SCR}}_d(f^n)={\mathcal{SCR}}_d(f)$ for all $n{\in}{\mathbb{N}}$.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.87-97
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• 2020

In this paper, we propose a novel neural relighting that infers a relighted rendering image based on the user-guided specular highlight map. The proposed network utilizes a pre-trained neural renderer as a backbone network learned from the rendered image of a 3D scene with various lighting conditions. We jointly optimize a 3D light position and its associated relighted image by back-propagation, so that the difference between the base image and the relighted image is similar to the user-guided specular highlight map. The proposed method has the advantage of being able to explicitly infer the 3D lighting position, while providing the artists' preferred 2D screen-space interface. The performance of the proposed network was measured under the conditions that can establish ground truths, and the average error rate of light position estimations is 0.11, with the normalized 3D scene size.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.286-287
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• 2020

Depth map is the most common way of expressing 3D space in immersive media. In this paper, we propose a post-processing method to improve the quality of depth map. In proposed method, a depth map is divided into segments, and the plane of each segment estimated using RANSAC. In order to increase the accuracy of the RANSAC process, we apply matching reliability of each pixel in depth map as a weighting factor.