• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.55-61
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• 2007

In this paper, we propose a three-dimensional(3D) active shape models for medical image segmentation. In order to build a 3D shape model, we need to generate a point distribution model(PDM) and select corresponding landmarks in all the training shapes. The manual determination method, two-dimensional(2D) method, and limited 3D method of landmark correspondences are time-consuming, tedious, and error-prone. In this paper, we generate a 3D statistical shape model using the 3D model generation method of a distance transform and a tetrahedron method for landmarking. After generating the 3D model, we extend the shape model training and gray-level model training of 2D active shape models(ASMs) and we use the integrated modeling process with scale and gray-level models for the appearance profile to represent the local structure. Experimental results are comparable to those of region-based, contour-based methods, and 2D ASMs.

• The korean journal of orthodontics
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• v.38 no.6
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• pp.427-436
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• 2008

Objective: The purpose of this study is to compare landmark position between cephalometric radiography and midsagittal plane projected images from 3 dimensional (3D) CT. Methods: Cephalometric radiographs and CT scans were taken from 20 patients for treatment of mandibular prognathism. After selection of land-marks, CT images were projected to the midsagittal plane and magnified to 110% according to the magnifying power of radiographs. These 2 images were superimposed with frontal and occipital bone. Common coordinate system was established on the base of FH plane. The coordinate value of each landmark was compared by paired t test and mean and standard deviation of difference was calculated. Results: The difference was from $-0.14{\pm}0.65$ to $-2.12{\pm}2.89\;mm$ in X axis, from $0.34{\pm}0.78$ to $-2.36{\pm}2.55\;mm$ ($6.79{\pm}3.04\;mm$) in Y axis. There was no significant difference only 9 in X axis, and 7 in Y axis out of 20 landmarks. This might be caused by error from the difference of head positioning, by masking the subtle end structures, identification error from the superimposition and error from the different definition.

• The korean journal of orthodontics
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• v.35 no.5 s.112
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• pp.388-397
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• 2005

The purpose of this study was to redefine the cephalometric landmarks in three-dimensional (3D) images, which are used in orthodontic cephalometric radiography, and to evaluate the reproducibility of each landmark for 3D cephalometric analysis. Eighteen CT scans were taken at the Department of Diagnostic Radiology at Seoul National University Dental Hospital and manipulated with V works 4.0(Cybermed Inc., Seoul, Korea). The coordinate system was established using 7 reference points, with no more than 4 points on the same plane. These 7 points were generated as a volume model, the voxel size of which was 4 by 4 by 2 (threshold value=639). The cephalometric landmarks were selected at the multiplanar reformation (MPR) window on the volume mode of V works 4.0. The selected landmarks were exported to V surgery (Cybermed Inc., Seoul, Korea) for the calculation of coordinate values. All the data were taken twice with a lapse of 2 weeks by one investigator The reproducibility of each landmark was $0.17\~1.21mm$ in the x axis, $0.30\~1.53mm$. In the y axis, and $0.27\~1.81mm$ in the z axis. In all three axes, the range of error was similar. These error ranges were acceptable with regards to the pixel space and slice thickness. The most reproducible points were 1 points which were selected on the basis of the volume model. The least reproducible points were J points that were defined by sutures.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.479-484
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• 2012

Geometric effect of landmarks to the navigation error is investigated in the two-dimensional line-of-sight measurement based vision navigation system. DOP is derived between line-of-sight measurement error and navigation solution error. For cases of three landmarks in an area, variations of the DOP were observed through computer simulations. Vision navigation system experiments were performed for the cases. Simulation and experimental results show that navigation solution errors have similar trend to DOP values of the simulation.

• The korean journal of orthodontics
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• v.47 no.1
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• pp.50-58
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• 2017

Introduction: Identifying menton (Me) on posteroanterior cephalograms and three-dimensional (3D) cone-beam computed tomography (CBCT) images is difficult, because the midpoint of the symphyseal area is not identifiable after the mandibular symphysis fuses at an early age. The aim of this study was to evaluate the reliability of the identification of the genial tubercle (GT) in patients with mandibular asymmetry and to compare it with that of the traditional landmark, Me. Methods: The samples comprised 20 CBCT images of adults with mandibular asymmetry. Two examiners performed the identifications and measurements. Me and GT were marked, and the anteroposterior, vertical, and transverse distances to the three reference planes were measured on 3D-reconstructed CBCT images. The intra- and inter-examiner reliability of landmark identification of Me and GT were assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots. Results: The Me and GT landmarks showed excellent reliability ($ICC{\geq}0.993$) three-dimensionally. In the transverse evaluation, the ICC values of the GT (range, 0.997-0.999) tended to be slightly higher than those of Me (range, 0.993-0.996). In the Bland-Altman plots for the two separate assessments, Me showed a maximum error of 1.76 mm in the transverse direction, whereas the GT showed a maximum error of 0.96 mm in the 95% limit. Conclusions: Our results suggest that both Me and GT are clinically reliable and equally useful landmarks for the evaluation of mandibular asymmetry on CBCT images.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.401-402
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• 2007

In this paper, we propose an automatic method to finding corresponding points. One 2D image can be changed 3D shape by 3D model. The main idea is using gabor wavelet values from 3D model. And Elastic Bunch Graph Matching algorithm is more stable in 3D model.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.212-214
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• 2021

In a society with Covid-19 as part of our daily lives, we had to adapt ourselves to a new reality to maintain our lifestyles as normal as possible. An example of this is teleworking and online classes. However, several issues appeared on the go as we started the new way of living. One of them is the doubt of knowing if real people are in front of the camera or if someone is paying attention during a lecture. Therefore, we encountered this issue by creating a 3D reconstruction tool to identify human faces and expressions actively. We use a web camera, a lightweight 3D face model, and use the 2D facial landmark to fit expression coefficients to drive the 3D model. With this Model, it is possible to represent our faces with an Avatar and fully control its bones with rotation and translation parameters. Therefore, in order to reconstruct facial expressions during online meetings, we proposed the above methods as our solution to solve the main issue.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.116-124
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• 2011

A service robot can identify its own position relative to landmarks, the locations of which are known in advance. The main contribution of this research is that it gives various ways of making the self-localizing error smaller by referring to special landmarks which are developed as high gain reflection material and coded array associations. In this paper, the authors propose a set of indices to evaluate the accuracy of self-localizing methods using the selective reflection landmark and infrared projector, and the indices are derived from the sensitivity enhancement using 3D distortion calibration of camera. And then, the accurarcy of self-localizing a mobile robot with landmarks based on the indices is evaluated, and a rational way to minimize to reduce the computational cost of selecting the best self-localizing method. The simulation results show a high accuracy and a good performance.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.2
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• pp.149-163
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• 1994

A novel method of dimensional measurement using machine vision, which is called Landmark Tracking System, has been developed. Its advantages come form tracking only the bright, standard shaped "landmarks" which are made from retroreflective sheets. In the design of the LTS, it is essential to know the relationship between optical parameters and their influence on system performance. Such optical parameters include the brightness of landmark image, the illumination system design, and the choice of imaging optics. And the performance of retroreflective material also plays important role in the LTS performances. Influences of such optical parameters on LTS's dimensional measurement characteristics are investigated, with respect to the retroreflective material, the imaging optics, and the illumination system. Measuremtn errors due to parameter variations are also analyzed. Experiments are performed with a LTS prototype. Retroreflective characteristics are verified, and the LTS's measurement performances are measured in the form of repeatability and accuracy. Experimental results shgow that the LTS has repeatability better than 1/30,000 of a field of view(30 degrees), and accuracy better tha 1/3,000 of a field fo view.d fo view.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.389-394
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localization technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.