• Journal of Biomedical Engineering Research
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• v.29 no.6
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• pp.431-435
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• 2008

Quantitative information of a three dimensional(3D) kinematics of joint is very useful in knee joint surgery, understanding how knee kinematics related to joint injury, impairment, surgical treatment, and rehabilitation. In this paper, an automated 2D/3D image matching technique was developed to estimate the 3D in vivo knee kinematics using dual X-ray images. First, a 3D geometric model of the knee was reconstructed from CT scan data. The 3D in vivo position and orientation of femoral and tibial components of the knee joint could be estimated by minimizing the pixel by pixel difference between the projection images from the developed 3D model and the given X-ray images. The accuracy of the developed technique was validated by an experiment with a cubic phantom. The present 2D/3D image matching technique for the estimation of in vivo joint kinematics could be useful for pre-operative planning as well as post-operative evaluation of knee surgery.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.466-469
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• 2005

Recently, in computer graphics, researches on 3D animations have been very active. One of the important research areas in 3D animation is animation of human being. Implicit surface model is convient for modeling objects composed of complicated surface such as 3D characters and liquids. Moreover, it can represent various forms of surfaces using a relatively small amount of data. In this paper, we propose a method of facial model generation using Implicit Primitive.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1239-1246
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• 2003

Registration is the process aligning the range data sets from different views in a common coordinate system. In order to achieve a complete 3D model, we need to refine the data sets after coarse registration. One of the most popular refinery techniques is the iterative closest point (ICP) algorithm, which starts with pre-estimated overlapping regions. This paper presents an improved ICP algorithm that can automatically register multiple 3D data sets from unknown viewpoints. The sensor projection that represents the mapping of the 3D data into its associated range image is used to determine the overlapping region of two range data sets. By combining ICP algorithm with the sensor projection constraint, we can make an automatic registration of multiple 3D sets without pre-procedures that are prone to errors and any mechanical positioning device or manual assistance. The experimental results showed better performance of the proposed method on a couple of 3D data sets than previous methods.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.29 no.3
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• pp.163-168
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• 2003

Three-dimensional solid model has not been widely used in surgical prediction of orthognathic surgery because frequent artifacts from occlusal restorations or prosthesis limited the usefulness of simulated surgery involving occlusion. We prepared three-dimensional(3D) solid model from CT data and integrated the 3D solid model with dental cast using a face-bow transfer technique combined with skeletal reference measurement and confirmation with cephalometric radiographs. With this simple and easy method, it was possible to predict bony interference between the proximal and distal segment of the mandible so that we can prevent condylar displacement after sagittal split ramus osteotomy of the mandible with prominent asymmetry. The method error was within 2mm and it seemed to be useful in preoperative planning for maxillofacial surgery with maxillo-mandibular occlusal change.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.655-669
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• 2019

Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.217-224
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• 2013

We developed a time-lapse inversion using new cross-model constraints based on change ratio and resolution of model parameters. The cross-model constraint based on change ratio imposes the same penalty on the model parameters with equal change ratio. This constraint can emphasize the model parameters with significant change regardless of their increase or decrease. The resolution cross-model constraint imposes a small penalty on the model parameters with poor resolution, but a large penalty on the model parameters with good resolution. Thus, the model parameter with poor resolution can be effectively identified in the inversion result if they are significantly changed with time. Through the numerical tests for 3D resistivity monitoring data sets, the performance of these two cross-model constraints was confirmed. Finally, for the safety estimation of a sea dyke, we applied the developed time-lapse inversion to the 3D resistivity monitoring data that were acquired at a sea dike located in western coastal area of Korea. The result of time-lapse inversion suggested that there were no significant changes at the sea dike during the monitoring period.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.787-800
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• 2021

Three-dimensional (3D) object classification tasks using point clouds are widely used in 3D modeling, face recognition, and robotic missions. However, processing raw point clouds directly is problematic for a traditional convolutional network due to the irregular data format of point clouds. This paper proposes a pointwise convolution neural network (CNN) structure that can process point cloud data directly without preprocessing. First, a 2D convolutional layer is introduced to percept coordinate information of each point. Then, multiple 2D convolutional layers and a global max pooling layer are applied to extract global features. Finally, based on the extracted features, fully connected layers predict the class labels of objects. We evaluated the proposed pointwise CNN structure on the ModelNet10 dataset. The proposed structure obtained higher accuracy compared to the existing methods. Experiments using the ModelNet10 dataset also prove that the difference in the point number of point clouds does not significantly influence on the proposed pointwise CNN structure.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.29-34
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• 2005

Aerial photogrammetry, which is one of the most frequent used technology in mapping and surveying, has been appreciated for its work flow and accuracy to generate 2D and 3D geospatial data. In aerial photograrnrnetry, more than two photographs are taken over the same target area in different position with overlap. Using these photographs and minimum number of ground control points, 3D stereo model is so formed that the ground surface in reality is reconstructed through analogue/analytical plotter or digital photogrammetry system. In case of digital photogrammetry system, 3D geospatial data could be automatically extracted in partial. Recently, in the advent of aerial digital camera such as ADS40 and DMC, digital photogrammetry system will be in the frist place for generating 3D geospatial data. In this paper, we experimentally generated 3D geospatial data using digital photograrnrnetry system in the aspect of work flow.

• KSCI Review
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• v.14 no.2
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• pp.147-152
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• 2006

Data size of moving current GIS great exponentially from 2D to 3D and the processing speed becomes slow thereby and user's real time rendering request is growing. Have problem that time and expense to process data of bulky quantity produce constraint condition of the processing speed. third dimension processing skill, virtual reality processing skill etc. and third dimension GIS about space data of bulk much overmuch to materialize. In this paper DEM data that acquire from satellite or aviation solve these problem embody virtual city in web save topography information that visualization to 3D visualization by VRML, and use modelling tool and acquire 3D campus information for building and road. 3D information acquired this to express texture and natural gifts that have truth stuff more to thing through near texture mapping work 3D imagination illustration of web based embody can.

• Journal of Fashion Business
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• v.10 no.6
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• pp.28-37
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• 2006

The purpose of this work is to present three-dimensional models of plain fabrics having various warp and filling yarn diameters. In order to simulate a woven fabric, a 3-dimensional CAD software with NURBS modeling capability was used. Final rendering was performed on the fabric model. It was demonstrated that the changes in yarn diameter could be three-dimensionally modeled through the use of fabric geometry and the 3D CAD. A short RhinoScript program was composed to implement the data importing and model building on the 3D CAD.