• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.443-454
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• 2019

In recent years, there has been active research on a recommender system that considers three or more inputs in addition to users and goods, making it a multi-dimensional array, also known as a tensor. The main issue with using tensor is that there are a lot of missing values, making it sparse. In order to solve this, the tensor can be shrunk using the tensor decomposition algorithm into a lower dimensional array called a factor matrix. Then, the tensor is reconstructed by calculating factor matrices to fill original empty cells with predicted values. This is called tensor reconstruction. In this paper, we propose a user-based Top-K recommender system by normalized PARAFAC tensor reconstruction. This method involves factorization of a tensor into factor matrices and reconstructs the tensor again. Before decomposition, the original tensor is normalized based on each dimension to reduce overfitting. Using the real world dataset, this paper shows the processing of a large amount of data and implements a recommender system based on Apache Spark. In addition, this study has confirmed that the recommender performance is improved through normalization of the tensor.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1923-1928
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• 2017

This paper is a study on error correction for three-dimensional shape reconstruction based on factorization method. The existing error correction method based on factorization has a limitation of correction because it is optimized globally. Thus in this paper, we propose our new method which can find and correct the only major error influence factor toward three-dimensional reconstructed shape instead of global approach. We define the error-influenced factor in two-dimensional re-projection deviation space and directly control the error components. In addition, it is possible to improve the error correcting performance by recursively applying the above process. This approach has an advantage under noise because it controls the major error components without depending on any geometric information. The performance evaluation of the proposed algorithm is verified by simulation with synthetic and real image sequence to demonstrate noise robustness.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.205-212
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• 2003

Many people are exposed to accidents by vehicles or sports. The most frequent injuries by these accidents is concerned with a knee joint. The three-dimensional surface model of a knee is needed for dynamic analysis of knee motion and knee reconstruction. three-dimensional motion data of a knee joint were obtained using X-ray and precise magnetic sensors. The surface data of a femur and a tibia were obtained using cross-sectional pictures by CT. The three-dimensional surface models of a femur and a tibia were made by the method of optimal triangular patch. Using obtained motion data, we simulated the motion of three-dimensional knee joint model.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.804-809
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• 2004

It is essential to calibrate a camera in order to recover 3-dimensional reconstruction from uncalibrated images. This paper proposes a new technique of the camera calibration using a homography between the planar patterns image taken by the camera, which is located at the three planar patterns image. Since the proposed method should be computed from the homography among the three planar patterns from a single image, it is implemented more easily and simply to recover 3D object than the conventional. Experimental results show the performances of the proposed method are the better than the conventional. We demonstrate the examples of 3D reconstruction using the proposed algorithm from image sequence.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.74-82
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• 2008

This paper investigates chrominance reconstruction methods that reconstruct subsampled chrominance information efficiently using the correlation between luminance and chrominance components in the decompression process of compressed images, and analyzes drawbacks involved in the adaptive-weighted 2-dimensional linear interpolation among the methods, which shows higher efficiency in the view of computational complexity than other methods. To improve the drawback that the spatial frequency distribution is not considered for the decompressed image and to support the application on a low-performance system in behalf of 2-dimensional linear interpolation, this paper proposes the multi-mode reconstruction method which uses three reconstruction methods having different computational complexity from each other according to the degree of edge response of luminance component. The performance evaluation on a development platform for embedded systems showed that the proposed reconstruction method supports the similar level of image quality for decompressed images while reducing the overall computation time for chrominance reconstruction in comparison with the 2-dimensional linear interpolation.

• Korean Journal of Bronchoesophagology
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• v.18 no.2
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• pp.49-55
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• 2012

Background and Objectives This study was conducted to gather three dimensional images from computed tomogram in detecting and gaining information about fish bones. Materials and Methods Thirty-nine fish bones and 2 chicken leg bones were used. Bones sandwiched between the cotton sheets were placed into the 3 plastic boxes. Computed tomogram of the bones in the boxes were reconstructed three-dimensionally by Xelis (Infinitt, Korea) to make images of MPR, MIP and VR images. The images were compared with real chicken bones and fish bones as to possibility of detection, finding of location and orientation, and evaluation of shape and calculation of size. Results All 41 bones were detected in all reconstructed images. Distance to the bones from reference point can be measured and orientation can be checked. Shapes were similar between matched images of all real bones. Conclusion The results indicate the usefulness of 3D reconstruction technique in getting informations about fish bones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1111-1116
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• 2009

In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.93-100
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• 2001

The three dimensional(3D) reconstruction from two dimensional(2D) image data is using in many fields such as RPD(Rapid Product Development) and reverse engineering. In this paper, the main step of 3D reconstruction is comprised of two steps : image processing step and B-spline surface approximation step. In the image processing step, feature points of each cross-section are obtained by means of several image processing technologies. In the B-spline surface approximation step, using the data of feature points obtained in the image processing step, the control points of B-spline surface are obtained, which are used for IGES file of 3D CAD model.