• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.391-394
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• 2005

In this paper, we present an approach that is able to reconstruct 3 dimensional metric models from un-calibrated images acquired by a freely moved camera system. If nothing is known of the calibration of either camera, nor the arrangement of one camera which respect to the other, then the projective reconstruction will have projective distortion which expressed by an arbitrary projective transformation. The distortion on the reconstruction is removed from projection to metric through self-calibration. The self-calibration requires no information about the camera matrices, or information about the scene geometry. Self-calibration is the process of determining internal camera parameters directly from multiply un-calibrated images. Self-calibration avoids the onerous task of calibrating cameras which needs to use special calibration objects. The root of the method is setting a uniquely fixed conic(absolute quadric) in 3D space. And it can make possible to figure out some way from the images. Once absolute quadric is identified, the metric geometry can be computed. We compared reconstruction image from calibrated images with the result by self-calibration method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.197-200
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper we applied super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and overlapped for high rate. We constructed the observation model between the HR images and LR images applied by the Maximum A Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Journal of Information Processing Systems
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• 제15권2호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.481-484
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• 2005

Inherent opportunities on research for restoring high resolution image from low resolution images are increasing in these days. Super resolution image reconstruction is the process of combining multiple low resolution images to form a higher resolution one. To achieve super resolution reconstruction, proper observation model which is based on subpixel shift information is required. In this context, the importance of the subpixel registration cannot be estimated because subpixel shift information cannot be obtained from original image. This paper presents a regularized adaptive super resolution reconstruction method based on phase correlated subpixel registration, where the Constrained Least Squares(CLS) Restoration is adopted as a post process.

• Archives of Plastic Surgery
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• 제49권1호
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• pp.91-98
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• 2022

Background Predicting the need for post-traumatic reconstruction of lower extremity injuries remains a challenge. Due to the larger volume of cases in adults than in children, the majority of the medical literature has focused on adult lower extremity reconstruction. This study evaluates predictive risk factors associated with the need for free flap reconstruction in pediatric patients following lower extremity trauma. Methods An IRB-approved retrospective chart analysis over a 5-year period (January 1, 2012 to December 31, 2017) was performed, including all pediatric patients (<18 years old) diagnosed with one or more lower extremity wounds. Patient demographics, trauma information, and operative information were reviewed. The statistical analysis consisted of univariate and multivariate regression models to identify predictor variables associated with free flap reconstruction. Results In total, 1,821 patients were identified who fit our search criteria, of whom 41 patients (2.25%) required free flap reconstruction, 65 patients (3.57%) required local flap reconstruction, and 19 patients (1.04%) required skin graft reconstruction. We determined that older age (odds ratio [OR], 1.134; P =0.002), all-terrain vehicle accidents (OR, 6.698; P<0.001), and trauma team activation (OR, 2.443; P=0.034) were associated with the need for free flap reconstruction following lower extremity trauma in our pediatric population. Conclusions Our study demonstrates a higher likelihood of free flap reconstruction in older pediatric patients, those involved in all-terrain vehicle accidents, and cases involving activation of the trauma team. This information can be implemented to help develop an early risk calculator that defines the need for complex lower extremity reconstruction in the pediatric population.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2718-2731
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• 2021

In the structural health monitoring of composite materials, in order to solve the ill-posed problem of impact force reconstruction, regularization techniques are often used to deal with it. Due to the poor convergence of the traditional Tikhonov regularization method, in order to accurately reconstruct the time history of the impact force, this paper improves Tikhonov regularization method and constructs homotopy function with strong convergence. Since the optimal regularization parameters need to be found in the homotopy function, the Newton downhill method is used to find the optimal parameters and the homotopy function can be calculated, which can accurately reconstruct the time history of the impact force. In order to verify the universality of the method in this paper, impact hammers of different materials were used in the experiment in this paper to study and compare the reconstruction effect of impact time history of different impact hammers.

• Journal of International Society for Simulation Surgery
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• 제1권1호
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• pp.19-22
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• 2014

As computer technology develops and this is applied to medical image field, three dimensional image reconstruction technology using computer simulation is utilized in various categories that include anatomical study and biomechanics study of human body. Especially orthopedic surgeons are able to investigate biomechanical function and be provided information for operations with this technology in terms of ligament reconstruction of knee. And this technology can be utilized in preparing preoperative planning and instructions and training. This review is about three dimensional image reconstruction technology which is utilized in ligament reconstruction of knee.

• ETRI Journal
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• 제30권5호
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• pp.753-755
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• 2008

In this letter, we propose a new histogram equalization technique for feature compensation in speech recognition under noisy environments. The proposed approach combines a signal-to-noise-ratio-dependent feature reconstruction method and the class histogram equalization technique to effectively reduce the acoustic mismatch present in noisy speech features. Experimental results from the Aurora 2 task confirm the superiority of the proposed approach for acoustic feature compensation.

• Journal of Ubiquitous Convergence Technology
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• 제1권1호
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• pp.9-17
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• 2007

Feature based stereo matching is an effective way to perform 3D building reconstruction. However, in urban scene, the cluttered background and various building structures may interfere with the performance of building reconstruction. In this paper, we propose a novel method to robustly reconstruct buildings on the basis of rectangle regions. Firstly, we propose a multi-scale linear feature detector to obtain the salient line segments on the object contours. Secondly, candidate rectangle regions are extracted from the salient line segments based on their local information. Thirdly, stereo matching is performed with the list of matching line segments, which are boundary edges of the corresponding rectangles from the left and right image. Experimental results demonstrate that the proposed method can achieve better accuracy on the reconstructed result than pixel-level stereo matching.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 춘계학술대회 논문집 센서 박막재료 반도체재료 기술교육
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• pp.119-123
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• 2002

A new modular Lateral Information Propagation Networks(LIPN) has been designed. The LIPN has shown to be useful for reconstruction of information[3]. The problem is the fact that only the small number of nodes can be implemented in a IC chip with the circuit VLSI technology. The proposed modular architecture is propagated the neural network through inter module connections. For such inter module connections, the host (computer or logic) mediates the exchange of information among modules. Also border nodes in each module have capacitors for temporarily retaining the information from outer modules. The LIPN with $4{\times}4$ modules has been designed and simulation of interpolation with the designed LIPN has been done.