• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1695-1700
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• 2005

In this paper, we propose an optimal thresholding method for the voxel coloring in the reconstruction of a 3D shape. Our purposed method is a new approach to resolve the trade-off error of the threshold value on determining the photo-consistency in the conventional method. Optimal thresholding value is decided to compare the surface voxel of photo-consistency with inside voxel on the optic ray of the center camera. As iterating the process of the voxels, the threshold value is approached to the optimal value for the individual surface voxel. And also, graph cut method is reduced to the surface noise on eliminating neighboring voxel. To verify the proposed algorithm, we simulated in the virtual and real environment. It is advantaged to speed up and accuracy of a 3D face reconstruction by applying the methods of optimal threshold and graph cut as compare with conventional algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.127-135
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• 2006

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, I propose the image-based 3D modeling system using calibrated camera. The proposed algorithm for rendering 3D model is consisted of three steps, camera calibration, 3D shape reconstruction and 3D surface generation step. In the camera calibration step, I estimate the camera matrix for the image aquisition camera. In the 3D shape reconstruction step, I calculate 3D volume data from silhouette using pyramidal volume intersection. In the 3D surface generation step, the reconstructed volume data is converted to 3D mesh surface. As shown the result, I generated relatively accurate 3D model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.426-429
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• 2004

To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.

• Current Optics and Photonics
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• v.2 no.4
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• pp.332-339
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• 2018

A new multi-frequency fringe projection method is proposed to reduce the nonlinear phase error in 3-D shape measurements using an adaptive compensation method. The phase error of the traditional fringe projection technique originates from various sources such as lens distortion, the nonlinear imaging system and a nonsinusoidal fringe pattern that can be very difficult to model. Inherent possibility of phase error appearing hinders one from accurate 3-D reconstruction. In this work, an adaptive compensation algorithm is introduced to reduce adaptively the phase error resulting from the fringe projection profilometry. Three different frequencies are used for generating the gratings of projector and conveyed to the four-step phase-shifting procedure to measure the objects of very discontinuous surfaces. The 3-D shape results show that this proposed technique succeeds in reconstructing the 3-D shape of any type of objects.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2379-2382
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• 2003

This paper describes the design, implementation and results of a unified non-rigid image registration method for the purposes of 3D shape reconstruction from serial section images. The proposed method uses active contour-based segmentation and compensation of radial distortion. Experimental results show that multiple images can be segmented and reconstructed by active single contour as well as intra- and inter-section registration.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.527-530
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• 2003

In this paper, we implemented the voxel coloring method to reconstruct 3D object from synthetic input Images. Then compare the result between using standard voxel coloring and using coarse-to-fine method. We compared using different voxel space site to see the difference of time processing and the result of 3D object. Photorealistic 3D object reconstruction is a challenging problem in computer graphics. Vexel coloring considered the reconstruction problem as a color reconstruction problem, instead of shape reconstruction problem. This method works by discretizing scene space into yokels, then traversed and colored those in special order. Also there is an extension of voxel coloring method far decreasing the amount of processing time called coarse-to-fine method. This. method works using low resolution instead of high resolution as input and after processing finish, apply some kind of search strategy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.919-920
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• 2013

• Journal of the Korea Computer Graphics Society
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• v.23 no.1
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• pp.57-65
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• 2017

In this paper, we present a dictionary learning method for reducing errors in point cloud models and reconstructing their geometry. For this, 3D feature information is extracted from the models which have a similar shape characteristic as the target model. Then a dictionary is constructed and the geometry is reconstructed using the dictionary. The presented method in this paper consists of the following three steps. First, a geometric patch is constructed from a similar model. Second, a morphological 3D feature of the acquired patch is learned. Third, a geometry reconstruction is performed using the learned dictionary. Finally, the error between the original model and the reconstruction result is calculated, and the accuracy of the reconstruction result is checked.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1159-1167
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• 2011

A novel 3D tube scanning technique is proposed. The proposed tube scanning technique is developed for a special tube inspection module which consists of four line-lasers and one camera. Using the scanning module, we can reconstruct the 360 degree shapes of the inner surfaces of a cylindrical tube. From an image frame captured by the camera, we reconstruct a partial tube model based on four laser triangulations. Then by aligning such partial models with respect to a reference tube axis, a complete 3D shape of the tube is reconstructed. The tube axis in each reconstructed frame is aligned with a 3D Euclidean transformation to the reference axis. Several experiments show that the proposed method can align multiple tube axes very accurately and reconstruct 3D shapes of a tube with very low shape distortion.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.264-272
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• 2019

In this paper, we propose a 3D human body reconstruction and refinement method from the frames extracted from a video to obtain natural and smooth motion in temporal domain. Individual frames extracted from the video are fed into convolutional neural network to estimate the location of the joint and the silhouette of the human body. This is done by projecting the parameter-based 3D deformable model to 2D image and by estimating the value of the optimal parameters. If the reconstruction process for each frame is performed independently, temporal consistency of human pose and shape cannot be guaranteed, yielding an inaccurate result. To alleviate this problem, the proposed method analyzes and interpolates the principal component parameters of the 3D morphable model reconstructed from each individual frame. Experimental result shows that the erroneous frames are corrected and refined by utilizing the relation between the previous and the next frames to obtain the improved 3D human reconstruction result.