• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.168-185
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• 2003

This paper presents a progressive algorithm that not only can narrow down the search domain in the course of face identification but also can fast reconstruct various 3D objects from a sketch drawing. The sketch drawing, edge-vertex graph without hidden line removal, which serves as input for reconstruction process, is obtained from an inaccurate freehand sketch of a 3D wireframe object. The algorithm is executed in two stages. In the face identification stage, we generate and classify potential faces into implausible, basis, and minimal faces by using geometrical and topological constraints to reduce search space. The proposed algorithm searches the space of minimal faces only to identify actual faces of an object fast. In the object reconstruction stage, we progressively calculate a 3D structure by optimizing the coordinates of vertices of an object according to the sketch order of faces. The progressive method reconstructs the most plausible 3D object quickly by applying 3D constraints that are derived from the relationship between the object and the sketch drawing in the optimization process. Furthermore, it allows the designer to change viewpoint during sketching. The progressive reconstruction algorithm is discussed, and examples from a working implementation are given.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.21-28
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• 2005

In this paper, we studied resolution to the FBP(Filtered Back-Propagation) tomographic image reconstruction algorithms. In order to analyze the resolution to the tomographic images, we derived ambiguity function to this algorithm which can be reconstructed from the improved FBP image reconstruction algorithm by using fixed coordinate system practically. Through simulation using this function, we determined the lateral and depth resolution quantitively and then analyzed respectively. Simulation results show that the lateral and depth resolution to the improved FBP image reconstruction algerian was determined $0.27\lambda\;and\;0.70\lambda$ at the 3dB, and also $0.89\lambda\;and\;0.96\lambda$ at the 6dB respectively. This results proved that improved FBP reconstruction algorithms for diffraction tomography of incident planar wave is useful to developed the tomographic image system, analyze the resolution to the tomographic images, we derived ambiguity function to this algerian which can be reconstructed from the improved FBP image reconstruction algorithm by using fixed coordinate system.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.55-59
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• 1989

A true three-dimensional cone-beam reconstruction (TTCR) algorithm for the complete sphere geometry is derived, which is applicable to the direct volume image reconstruction from 2-D cone-beam projections. The algorithm is based on the modified filtered backprojection technique which uses a set of 2-D space-invariant filters and is derived from the previously developed parallel-beam true three-dimensional reconstruction(TTR) algorithm. The proposed algorithm proved to be superior in spatial resolution compared with the parallel-beam TTR algorithm.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.711-721
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• 2012

The objective of this study is to propose an efficient 3D reconstruction method for developing a stereo-vision-based haptics system which can replace "robotic eyes" and "robotic touch." The haptic rendering for 3D images requires to capture depth information and edge information of stereo images. This paper proposes the 3D reconstruction methods using LoG(Laplacian of Gaussian) algorithm and DoG(Difference of Gaussian) algorithm for edge detection in addition to the basic 3D depth extraction method for better haptic rendering. Also, some experiments are performed for evaluating the CPU time and the error rates of those methods. The experimental results lead us to conclude that the DoG method is more efficient for haptic rendering. This paper may contribute to investigate the effective methods for 3D image reconstruction such as in improving the performance of mobile patrol robots.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.343-364
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• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1142-1148
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• 2019

Reconstruction of the three-dimensional (3D) environment is a key aspect of augmented reality and augmented virtuality, which utilize and incorporate a user's surroundings. Such reconstruction can be easily realized by employing a Kinect device. However, multiple Kinect devices are required for enhancing the reconstruction density and for spatial expansion. While employing multiple Kinect devices, they must be calibrated with respect to each other in advance, and a marker is often used for this purpose. However, a marker needs to be placed at each calibration, and the result of marker detection significantly affects the calibration accuracy. Therefore, a user-friendly, efficient, accurate, and marker-less method for calibrating multiple Kinect devices is proposed in this study. The proposed method includes a joint tracking algorithm for approximate calibration, and the obtained result is further refined by applying the iterative closest point algorithm. Experimental results indicate that the proposed method is a convenient alternative to conventional marker-based methods for calibrating multiple Kinect devices. Hence, the proposed method can be incorporated in various applications of augmented reality and augmented virtuality that require 3D environment reconstruction by employing multiple Kinect devices.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.83-90
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• 1999

In this paper, we studied resolution to the FBP and BFP image reconstruction algorithms for ultrasonic diffraction tomography. In order to analyze the resolution to the tomographic images which can be reconstructed from the modified FBP image reconstruction algorithm by using fixed coordinate system and BFP image reconstruction algorithm which is suitable for plane structure object, we derived ambiguity functions to these algorithms and then analyzed lateral and depth resolution through simulation respectively. Simulation results show that the lateral and depth resolution to the FBP image reconstruction algorithm and the BFP image reconstruction algorithm was determined 0.27 λ, 0.70 λ and 0.39 λ, 0.98 λ at the 3dB respectively. These results imply that modified FBP and BFP image reconstruction algorithms for diffraction tomography is useful in the tomographic image reconstruction.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.141-147
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• 2009

This paper presents a new fast algorithm, rotation-based method (RBM), for the reconstruction of 3 dimensional image for cone beam computerized tomography (CB CT) system. The system used cone beam has less exposure time of radioactivity than fan beam. The Three-Pass Shear Matrices (TPSM) is applied, that has less transcendental functions than the one-pass shear method to decrease a time of calculations in the computer. To evaluate the quality of the 3-D images and the time for the reconstruction of the 3-D images, another 3-D images were reconstructed by the radon transform under the same condition. For the quality of the 3-D images, the images by radon transform was shown little good quality than REM. But for the time for the reconstruction of the 3-D images REM algorithm was 35 times faster than radon transform. This algorithm offered $4{\sim}5$ frames a second. It meant that it will be possible to reconstruct the 3-D dynamic images in real time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.714-718
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• 2009

3D reconstruction of a human face from an image sequence remains an important problem in computer vision. We propose a method, based on a factorization algorithm, that reconstructs a 3D face model from short image sequences exhibiting rotational motion. Factorization algorithms can recover structure and motion simultaneously from one image sequence, but they usually require that all feature points be well tracked. Under rotational motion, however, feature tracking often fails due to occlusion and frame out of features. Additionally, the paucity of images may make feature tracking more difficult or decrease reconstruction accuracy. The proposed 3D reconstruction approach can handle short image sequences exhibiting rotational motion wherein feature points are likely to be missing. We implement the proposal as a reconstruction method; it employs image sequence division and a feature tracking method that uses Active Appearance Models to avoid the failure of feature tracking. Experiments conducted on an image sequence of a human face demonstrate the effectiveness of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.570-577
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• 2005

In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.