• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.500-506
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• 2014

A new 3-D reconstruction algorithm for the human face is proposed using the derivative Moir$\acute{e}$ topography which ensures fast and robust reconstruction even for rough surfaces. The Moir$\acute{e}$ interference fringe pattern is initially obtained through the projection Moir$\acute{e}$ topography based on phase shifting, and then differentiated to provide a full unwrapped phase map for a human face. $2{\pi}$ ambiguity, which has been a chronically unsolved problem with Moir$\acute{e}$ topography, is successfully surmounted by differentiating the Moir$\acute{e}$ fringe patterns both in x- and y-directions when the object is located in the x-y plane. A real human face is used for verifying the proposed derivative Moir$\acute{e}$ topography. A human face of 4 different phase-shifted images taken in the fixed plane is almost fully reconstructed in 3-D format in 0.1 mm lateral resolution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.281-288
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• 2016

The natural moving objects are the most non-rigid shapes with randomly time-varying deformation, and its types also very diverse. Methods of non-rigid shape reconstruction have widely applied in field of movie or game industry in recent years. However, a realistic approach requires moving object to stick many beacon sets. To resolve this drawback, non-rigid shape reconstruction researches from input video without beacon sets are investigated in multimedia application fields. In this regard, our paper propose novel CPSRF(Chained Partial Stereo Rigid Factorization) algorithm that can reconstruct a non-rigid 3D shape. Our method is focused on the real-time reconstruction of non-rigid 3D shape and motion from stereo 2D video sequences per frame. And we do not constrain that the deformation of the time-varying non-rigid shape is limited by a Gaussian distribution. The experimental results show that the 3D reconstruction performance of the proposed CPSRF method is superior to that of the previous method which does not consider the random deformation of shape.

• Journal of the Optical Society of Korea
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• v.19 no.3
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• pp.248-254
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• 2015

In this paper we propose an improved version of the computational integral imaging reconstruction (CIIR) for visualizing a partially occluded object by utilizing an image inpainting technique. In the proposed method the elemental images for a partially occluded three-dimensional (3D) object are recorded through the integral imaging pickup process. Next, the depth of occlusion within the elemental images is estimated using two different CIIR methods, and the weight mask pattern for occlusion is generated. After that, we apply our image inpainting technique to the recorded elemental images to fill in the occluding area with reliable data, using information from neighboring pixels. Finally, the inpainted elemental images for the occluded region are reconstructed using the CIIR process. To verify the validity of the proposed system, we carry out preliminary experiments in which faces are the objects. The experimental results reveal that the proposed system can dramatically improve the quality of a reconstructed CIIR image.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.5
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• pp.212-219
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• 2002

In this paper, the epipolar geometry, genera17y used as a pin-hole camera model, is newly adapted to our proposed method that enables the affine reconstruction of the 3D object from two projected views. The proposed method models the projective projection of inherent X-ray imaging system, obviates the need to attach artifirially constructed material on the body, and requires none of the prior-knowledge regarding to intrinsic and extrinsic parameters of two X-ray imaging systems. The optimum numerical solution is obtained by applying the least mean square estimator to corresponding points on two projected X-ray planes. The performance of this proposed method is Quantitatively analyzed using computer synthesized model of Cochlear implantation electrodes. In simulated experiments, the propnsed method is insensitive to the added random noise, the scaling factor change, the center point change, and rotational angular change between two projection planes, as well as enables the stable 3D reconstruction in least square sense even in worst testing cases.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1658-1667
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• 2008

Reconstruction of 3D objects from a single view image is generally an ill-posed problem because of the projection distortion. A monocular vision based 3D object localization method is proposed in this paper, which approximates an object on the ground to a simple bounding solid and works automatically without any prior information about the object. A spherical or cylindrical object determined based on a circularity measure is approximated to a bounding cylinder, while the other general free-shaped objects to a bounding box or a bounding cylinder appropriately. For a general object, its silhouette on the ground is first computed by back-projecting its projected image in image plane onto the ground plane and then a base rectangle on the ground is determined by using the intuition that touched parts of the object on the ground should appear at lower part of the silhouette. The base rectangle is adjusted and extended until a derived bounding box from it can enclose the general object sufficiently. Height of the bounding box is also determined enough to enclose the general object. When the general object looks like a round-shaped object, a bounding cylinder that encloses the bounding box minimally is selected instead of the bounding box. A bounding solid can be utilized to localize a 3D object on the ground and to roughly estimate its volume. Usefulness of our approach is presented with experimental results on real image objects and limitations of our approach are discussed.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07b
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• pp.1615-1618
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• 2005

In this paper, implementation of object-based multiview 3D display using object segmentation and adaptive disparity estimation is proposed and its performance is analyzed by comparison to that of the conventional disparity estimation algorithms. In the proposed algorithm, firstly we can get segmented objects by region growing from input stereoscopic image pair and then, in order to effectively synthesize the intermediate view the matching window size is selected according to the extracted feature value of the input stereo image pair. Also, the matching window size for the intermediate view reconstruction (IVR) is adaptively selected in accordance with the magnitude of the extracted feature value from the input stereo image pair. In addition, some experimental results on the IVR using the proposed algorithm is also discussed and compared with that of the conventional algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.261-264
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• 1993

To reconstruct the real 3-D shape from the 3-D measurement data from the multiple directions, the rconstruction of the object on the basis of the mosaic processing of the 3-D measurement data are proposed. In this method, to conduct the reconstruction, the connection points have to be identified among the over-lap area between adjacent 3-D data. In this study, the simple image matching method is adopted for the identification of connection points, and this method is verified from numerical experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

In this paper, we analyze geometrical relations of 3D shape reconstruction from 2D images taken under anne projection. The purpose of this research is to contribute to more accurate 3-D reconstruction under noise distribution by analyzing geometrically the 2D to 3D relationship. In situation for no missing feature points (FPs) or no noise in 2D image plane, the accurate solution of 3D shape reconstruction is blown to be provided by Singular Yalue Decomposition (SVD) factorization. However, if several FPs not been observed because of object occlusion and image low resolution, and so on, there is no simple solution. Moreover, the 3D shape reconstructed from noise-distributed FPs is peturbed because of the influence of the noise. This paper focuses on analysis of geometrical properties which can interpret the missing FPs even though the noise is distributed on other FPs.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.8-16
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• 2016

In the field of computer vision and robotics, bin picking is an important application area in which object pose estimation is necessary. Different approaches, such as 2D feature tracking and 3D surface reconstruction, have been introduced to estimate the object pose accurately. We propose a new approach where we can use both 2D image features and 3D surface information to identify the target object and estimate its pose accurately. First, we introduce a label detection technique using Maximally Stable Extremal Regions (MSERs) where the label detection results are used to identify the target objects separately. Then, the 2D image features on the detected label areas are utilized to generate 3D surface information. Finally, we calculate the 3D position and the orientation of the target objects using the information of the 3D surface.