• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.935-938
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• 2008

Three-dimensional (3D) display systems based on wavefront reconstruction are presented. To obtain the wavefront of 3D objects, we present holographic recording using temporally or spatially phase-shifting interferometer. In the 3D display systems, phase-only reconstruction using a spatial light modulator and an approach to increase the reconstructed power are presented.

• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.133-139
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• 2001

Since a great number of 2D engineering drawings are being used in industry and at the same time 3D CAD becomes popular in recent years, we need to reconstruct 3D CAD models from 2D legacy drawings. In this thesis, a combination of a feature recognition method and an expert system is suggested for the 3D solid model reconstruction. Modeling primitives of 3D CAD systems are recognized and constructed by using the pattern matching technique of the features modeling. Additional information for the 3D model reconstruction can be generated by extracting symbols or text entities which are related to form entities. For complex and indefinite cases which cannot be solved by the process of feature recognition, an expert system with a rule base has been used for decision-making. A 3D reconstruction system which recognizes 2D DXF drawing files has been implemented where models composed with protrusions, holes, and cutouts can be handled.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2363-2369
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• 2016

In this paper, we propose three-dimensional (3D) quick-response (QR) code generation technique using passive 3D integral imaging and computational integral imaging reconstruction technique. In our proposed method, we divide 2D QR code into 4 planes with different reconstruction depths and then we generate 3D QR code using synthetic aperture integral imaging and computational reconstruction. In this 3D QR code generation process, we use integral imaging which is one of 3D imaging technologies. Finally, 3D QR code can be scanned by reconstructing and merging 3D QR codes at 4 different planes with computational reconstruction. Therefore, the security level for QR code scanning may be enhanced when QR code is scanned. To show that our proposed method can improve the security level for QR code scanning, in this paper, we carry out the optical experiments and computational reconstruction. In addition, we show that 3D QR code can be scanned when reconstruction depths are known.

• The Journal of the Korea Contents Association
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• v.14 no.7
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• pp.1-9
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• 2014

Previous 2D-3D conversion methods to generate 3D stereo images from 2D sequence consist of labor-intensive procedures in their production pipelines. This paper presents an efficient 2D-3D conversion system based on scene structure reconstruction from image sequence. The proposed system reconstructs a scene space and produces 3D stereo images with texture re-projection. Experimental results show that the proposed method can generate precise 3D contents based on scene structure information. By using the proposed reconstruction tool, the stereographer can collaborate efficiently with workers in production pipeline for 3D contents production.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1004-1013
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• 2017

This paper presents a relationship between the number of curves and geometric parameters of a 3D object. Once the relationship is established, the number of closed curves that can reliably represent 3D object is derived. Inspired by Shannon-Nyquist Sampling Theorem, in this paper, approach for sampling rate (defined as the minimum number of curves) for 3D reconstruction is proposed. The relationship is straightforward, is suitable for application to 3D object overlaid with closed-continuous curves, and can achieve efficient 3D reconstruction system in practice. To substantiate the proposed approach, simulation results are provided and the results show that the number of curves can be decreased without loss of generality of characteristics of a target 3D object.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3121-3142
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• 2017

We present a method for 3D shape reconstruction of inextensible deformable surfaces from a single image. The key of our approach is to represent the surface as a 3D triangulated mesh and formulate the reconstruction problem as a sequence of Linear Programming (LP) problems. The LP problem consists of data constraints which are 3D-to-2D keypoint correspondences and shape constraints which are designed to retain original lengths of mesh edges. We use a closed-form method to generate an initial structure, then refine this structure by solving the LP problem iteratively. Compared with previous methods, ours neither involves smoothness constraints nor temporal consistency, which enables us to recover shapes of surfaces with various deformations from a single image. The robustness and accuracy of our approach are evaluated quantitatively on synthetic data and qualitatively on real data.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.51-56
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• 2016

In this paper, we present a three-dimensional (3-D) automatic target recognition system based on optical integral imaging reconstruction. In integral imaging, elemental images of the reference and target 3-D objects are obtained through a lenslet array or a camera array. Then, reconstructed 3-D images at various reconstruction depths can be optically generated on the output plane by back-projecting these elemental images onto a display panel. 3-D automatic target recognition can be implemented using computational integral imaging reconstruction and digital nonlinear correlation filters. However, these methods require non-trivial computation time for reconstruction and recognition. Instead, we implement 3-D automatic target recognition using optical cross-correlation between the reconstructed 3-D reference and target images at the same reconstruction depth. Our method depends on an all-optical structure to realize a real-time 3-D automatic target recognition system. In addition, we use a nonlinear correlation filter to improve recognition performance. To prove our proposed method, we carry out the optical experiments and report recognition results.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.399-409
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• 2019

Three-dimensional (3D) human pose reconstruction from single-view image is a difficult and challenging topic. Existing approaches mostly process frame-by-frame independently while inter-frames are highly correlated in a sequence. In contrast, we introduce a novel spatial-temporal 3D human pose reconstruction framework that leverages both intra and inter-frame relationships in consecutive 2D pose sequences. Orthogonal matching pursuit (OMP) algorithm, pre-trained pose-angle limits and temporal models have been implemented. Several quantitative comparisons between our proposed framework and recent works have been studied on CMU motion capture dataset and Vietnamese traditional dance sequences. Our framework outperforms others by 10% lower of Euclidean reconstruction error and more robust against Gaussian noise. Additionally, it is also important to mention that our reconstructed 3D pose sequences are more natural and smoother than others.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.338-357
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• 2016

The recent advent of increasingly affordable and powerful 3D scanning devices capable of capturing high resolution range data about real-world objects and environments has fueled research into effective 3D surface reconstruction techniques for rendering the raw point cloud data produced by many of these devices into a form that would make it usable in a variety of application domains. This paper, therefore, provides an overview of the existing literature on surface reconstruction from 3D point clouds. It explains some of the basic surface reconstruction concepts, describes the various factors used to evaluate surface reconstruction methods, highlights some commonly encountered issues in dealing with the raw 3D point cloud data and delineates the tradeoffs between data resolution/accuracy and processing speed. It also categorizes the various techniques for this task and briefly analyzes their empirical evaluation results demarcating their advantages and disadvantages. The paper concludes with a cross-comparison of methods which have been evaluated on the same benchmark data sets along with a discussion of the overall trends reported in the literature. The objective is to provide an overview of the state of the art on surface reconstruction from point cloud data in order to facilitate and inspire further research in this area.

• 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.