• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.224-230
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• 2015

This manuscript presents a real-time solution for 3D human body reconstruction with multiple RGB-D cameras. The proposed system uses four consumer RGB/Depth (RGB-D) cameras, each located at approximately $90^{\circ}$ from the next camera around a freely moving human body. A single mesh is constructed from the captured point clouds by iteratively removing the estimated overlapping regions from the boundary. A cell-based mesh construction algorithm is developed, recovering the 3D shape from various conditions, considering the direction of the camera and the mesh boundary. The proposed algorithm also allows problematic holes and/or occluded regions to be recovered from another view. Finally, calibrated RGB data is merged with the constructed mesh so it can be viewed from an arbitrary direction. The proposed algorithm is implemented with general-purpose computation on graphics processing unit (GPGPU) for real-time processing owing to its suitability for parallel processing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.4
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• pp.795-798
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• 2007

In this paper, we propose an image reconstruction method utilizing an optimized adaptive interpolation kernel along with a 2D M-channel perfect reconstruction filter bank (M-ch PR-FB) structure. In particular, the proposed approach leads to construction of a sharper image than a direct conversion, still preserving high frequency components of the original image through the subband processing of the 2D M-ch PR-FB. Finally, the image quality of the proposed approach is demonstrated by comparing with those of the direct methods using conventional interpolation kernels.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.4
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• pp.168-176
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• 2005

We propose a method for 3-dimensionally reconstructing an object using a line that includes the midpoint information from a single image. A pre-defined polygon is used as the primitive and the recovery is processed from a single image. The 3D reconstruction is processed by mapping the correspondence point of the primitive model onto the photo. In the recent work, the reconstructions of camera parameters or error minimizing methods through iterations were used for model-based 3D reconstruction. However, we proposed a method for the 3D reconstruction of primitive that consists of the segments and the center points of the segments for the reconstruction process. This method enables the reconstruction of the primitive model to be processed using only the focal length of various camera parameters during the segment reconstruction process.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.314-316
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• 1996

To diagnose cardiac malfunctions, various imaging techniques have been applied to heart : DSA(Digital Subtracted Angiography), Doppler Ultrasound, MR Angio. But it is difficult to observe three dimensional heart motion which is the most intuitive tool for diagnosis, only by using these methods. In this research, we have suggested 4-Dimensional reconstruction scheme of heart motion images that can be acquired by ECG-gated cine MR imaging. One cardiac cycle was devided into $9\sim15$ phases and for each phase 3D reconstructed volumn heart was made. We can observe 3D volumns along the cardiac cycle, time. So the results were 4-D reconstructed data.

• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.189-198
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• 1998

3D medical image reconstruction techniques are useful to figure out complex 3D structures from the set of 2D sections. In the paper, 3D medical image reconstruction system is constructed under PC environment and programmed based on modular programming by using Visual C++ 4.2. The whole procedures are composed of data preparation, gradient estimation, classification, shading, transformation and ray-casting & compositing. Three speed optimization techniques are used for accelerating 3D medical image reconstruction technique. One is to reduce the rays when cast rays to reconstruct 3D medical image, another is to reduce the voxels to be calculated and the other is to apply early ray termination. To implement 3D medical image reconstruction system based on PC, speed optimization techniques are experimented and applied.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.7
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• pp.71-79
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• 2002

A new rapid prototyping process, Variable Lamination Manufacturing using a 4-axis-controlled hotwire cutter and expandable polystyrene foam sheet as a laminating material of the part (VLM-S), has been developed to reduce building time and to improve the surface finish of parts. The objective of this study is to reconstruct the surface of the original 3D CAD model in order to generate mid-slice data using the advancing front technique. The generation of 3D layers by a 4 axis-controlled hot-wire cutter requires a completely different procedure to generate toolpath data unlike the conventional RP CAD systems. The cutting path data for VLM-S are created by VLM-Slicer, which is a special CAD/CAM software with automatic generation of 3D toolpath. For the conventional sheet type system like LOM, the STL file would be sliced into 2D data only. However, because of using the thick layers and a sloping edge with the firstorder approximation between the top and bottom layers, VLM-Slicer requires surface reconstruction, mid-slice, and the toolpath data generation as well as 2D slicing. Surface reconstruction demands the connection between the two neighboring cross-sectional contours using the triangular facets. VLM-S employs thick layers with finite thickness, so that surface reconstruction is necessary to obtain a sloping angle of a side surface and the point data at a half of the sheet thickness. In the process of the toolpath data generation the surface reconstruction algorithm is expected to minimize the error between the ruled surface and the original parts..

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.173-180
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• 2006

A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.388-394
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• 2014

In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.8-14
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• 2009

In this paper, a convex optimization technique, which is based on the generalized quantization constraint (GQC), is proposed in the compressive sensing reconstruction using quantized measures. The set size of the proposed GQC can be controlled, and through extensive numerical simulations based on the uniform scalar quantizers, the CS reconstruction errors are improved by 3.4-3.6dB compared to the traditional QC method for the CS problems of m/klogn > 2.