• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.99-106
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• 2016

In this paper, we will discuss about correction method of missing data on noisy observation matrix and uncertainty analysis for the potential noise. In situations without missing data in an observation matrix, this solution is known to be accurately induced by SVD (Singular Value Decomposition). However, usually the several entries of observation matrix have not been observed and other entries have been perturbed by the influence of noise. In this case, it is difficult to find the solution as well as cause the 3D reconstruction error. Therefore, in order to minimize the 3D reconstruction error, above all things, it is necessary to correct reliably the missing data under noise distribution and to give a quantitative evaluation for the corrected results. This paper focuses on a method for correcting missing data using geometrical properties between 2D projected object and 3D reconstructed shape and for estimating a noise level of the observation matrix using ranks of SVD in order to quantitatively evaluate the performance of the correction algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.174-182
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• 2003

Recently, medical imaging has taken interest on CAD based solution for anatomical part fabrication or finite element analysis of human body. In principle, contours representing object boundary are obtained through image processing techniques. Surface models are then approximated by a skinning method. For this, various methods should be applied to medical images and contours. The major bottleneck of the reconstruction is to remove shape inconsistency between contours and to generate the branching surface. In order to solve these problems, bi-directional smoothing and the composite contour generation method are proposed. Bi-directional smoothing has advantage of removing the shape inconsistency between contours and minimizing shrinkage effect with a large number of iterations. The composite contour by the proposed method ensures smooth transition in branching region.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.17-25
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• 2019

In this paper, we introduce the technology to convert a single human image into a fashion show animation video clip. The technology can help the customers confirm the dynamic fitting result when combined with the virtual try on technique as well as the interesting experience to a normal person of being a fashion model. We developed an extended technique of full human 2D to 3D inverse modeling based on SMPLify human body inverse modeling technique, and a rigged model animation method. The 3D shape deformation of the full human from the body model was performed by 2 part deformation in the image domain and reconstruction using the estimated depth information. The quality of resultant animation videos are made to be publically available for evaluation. We consider it is a promising approach for commercial application when supplemented with the post - processing technology such as image segmentation technique, mapping technique and restoration technique of obscured area.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.21-27
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• 2002

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. A number of visual or optical technologies have been successfully applied to measure three-dimensional surfaces. However, those conventional visual or optical methods have inherent shortcomings such as occlusion and variant surface reflection. X-ray vision system can be a good solution to these conventional problems, since we can extract the volume information including both the surface geometry and the inner structure of any objects. In the x-ray system, the surface condition of an object, whether it is lambertian or specular, does not affect the inherent characteristics of its x-ray images. In this paper, we propose a three-dimensional x-ray imaging method to reconstruct a three dimensional structure of an object out of two dimensional x-ray image sets. To achieve this by the proposed method, two or more x-ray images projected from different views are needed. Once these images are acquired, the simultaneous algebraic reconstruction technique(SART) is usually utilized. Since the existing SART algorithms have several shortcomings such as low performance in convergence and different convergence within the reconstruction volume of interest, an advanced SART algorithm named as USART(uniform SART) is proposed to avoid such shortcomings and improve the reconstruction performance. Because, each voxel within the volume is equally weighted to update instantaneous value of its internal density, it can achieve uniform convergence property of the reconstructed volume. The algorithm is simulated on various shapes of objects such as a pyramid, a hemisphere and a BGA model. Based on simulation results the performance of the proposed method is compared with that of the conventional SART method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.113-122
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• 2020

Noise affects the accuracy of three-dimensional shape recovery. Its occurrence is unpredictable and depends on several mechanical, environmental, and other factors. When two-dimensional image sequences are obtained for shape from focus (SFF), mechanical vibration occurs in the translational stage, causing an error in the three-dimensional shape recovery. To address this issue, mechanical vibration is modeled using Newton's second law and the principle of the rack and pinion gear. Then, an optimal sampling step size considering the mechanical vibration is suggested through theoretical demonstration. Experiments conducted with real objects verify the effectiveness of the proposed sampling step size. In this paper, in a realistic environment with noise, the potential of obtaining more accurate three-dimensional reconstruction results of the objects is explored by acquiring the optimal sampling step size, which improves the sampling step size relative to those reported in a previous study performed under similar conditions.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1126-1134
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• 2017

A variety of medical service applications in the field of the Internet of Things (IoT) are being studied. Segmentation is important to identify meaningful regions in images and is also required in 3D images. Previous methods have been based on gray value and shape. The Visible Korean dataset consists of serially sectioned high-resolution color images. Unlike computed tomography or magnetic resonance images, automatic segmentation of color images is difficult because detecting an object's boundaries in colored images is very difficult compared to grayscale images. Therefore, skilled anatomists usually segment color images manually or semi-automatically. We present an out-of-core 3D segmentation method for large-scale image datasets. Our method can segment significant regions in the coronal and sagittal planes, as well as the axial plane, to produce a 3D image. Our system verifies the result interactively with a multi-planar reconstruction view and a 3D view. Our system can be used to train unskilled anatomists and medical students. It is also possible for a skilled anatomist to segment an image remotely since it is difficult to transfer such large amounts of data.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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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.

• Smart Media Journal
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• v.3 no.4
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• pp.22-27
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• 2014

Three-dimensional image reconstruction allows us to represent real objects in the virtual space and observe the objects at arbitrary view points. This technique can be used in various application areas such as education, culture, and art. In this paper, we propose an implementation method of the high-quality three-dimensional object using multiple Kinect cameras released from Microsoft. First, We acquire color and depth images from triple Kinect cameras; Kinect cameras are placed in front of the object as a convergence form. Because original depth image includes some areas where have no depth values, we employ joint bilateral filter to refine these areas. In addition to the depth image problem, there is an color mismatch problem in color images of multiview system. In order to solve it, we exploit an color correction method using three-dimensional geometry. Through the experimental results, we found that three-dimensional object which is used the proposed method is more naturally represented than the original three-dimensional object in terms of the color and shape.

• New Physics: Sae Mulli
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• v.68 no.11
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• pp.1275-1280
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• 2018

We demonstrated transmission direct phase-measuring deflectometry (DPMD) with a specular phase object having discontinuous surfaces by using two displays and a two-dimensional array detector for display and by recording the distorted fringe patterns. Three-dimensional (3D) information was obtained by calculating the height map directly from the phase information. We developed a mathematical model of the phase-height relationship in transmission DPMD. Unlike normal transmission deflectometry, this method supports height measurement directly from the phase. Compared with other 3D measurement techniques such as interferometry, this method has the advantages of being inexpensive and easy to implement.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.129-135
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• 2022

Real human digital models appear more and more frequently in VR/AR application scenarios, in which real-time markerless face capture animation of personalized virtual human faces is an important research topic. The traditional way to achieve personalized real human facial animation requires multiple mature animation staff, and in practice, the complex process and difficult technology may bring obstacles to inexperienced users. This paper proposes a new process to solve this kind of work, which has the advantages of low cost and less time than the traditional production method. For the personalized real human face model obtained by 3D reconstruction technology, first, use R3ds Wrap to topology the model, then use Avatary to make 52 Blend-Shape model files suitable for AR-Kit, and finally realize real-time markerless face capture 3D real human on the UE4 platform facial motion capture, this study makes rational use of the advantages of software and proposes a more efficient workflow for real-time markerless facial motion capture of personalized 3D real human models, The process ideas proposed in this paper can be helpful for other scholars who study this kind of work.