• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.4 s.152
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• pp.542-553
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• 2006

The purpose of this study were to analyse of craniofacial shape by 3D and to develope of head models for Korean adults with gender and age groups. The 3D measurement technique adapted in this study was a novel approach compared that the same technique has been commonly used in measuring human bodies. The data and the model of head analysis can be used as a basic reference in developing various head related items such as hat, helmet, gas mask, ear phone, and etc. In this study, heads of 836 Korean adults were measured in 3D, analyzed by statistical methods, and modelized in 3D by gender and age groups. From the basic statistical data analysis, vertex-tragion and the length between the pupils were the longest in their twenties for both men and women, and grew shorter in elderly groups. In all categories, a significant difference appeared between men and women in their 20's, but the differences were less noticeable in elderly groups. Compared to the one size standard head model of the Korea Occupational Safety and Health Agency, the above three-dimensional standard head model would provide a more through fit because gender and age groups were sub-divided and analyzed in 3D.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.150-152
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• 2003

Laser scanned lidar data record 3D surface information in detail. Exploring valuable spatial information from lidar data is a prerequisite task for its applications, such as DEM generation and 3D building model reconstruction. However, the inherent spatial information is implicit in the abundant, densely and randomly distributed point cloud. This paper proposes a novel method to organize point cloud data, so that further analysis or feature extraction can proceed based on a well organized data model. The principle of the proposed algorithm is to segment point cloud into 3D planes. A split and merge segmentation based on the octree structure is developed for the implementation. Some practical airborne and ground lidar data are tested for demonstration and discussion. We expect this data organization could provide a stepping stone for extracting spatial information from lidar data.

• Spatial Information Research
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• v.18 no.5
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• pp.93-105
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• 2010

Spatial neighborhoods are spaces which are relate to target space. A 3D spatial query which is a function for searching spatial neighborhoods is a significant function in spatial analysis. Various methodologies have been proposed in related these studies, this study suggests an adjacent based methodology. The methodology of this paper implements topological data for represent a adjacency via using network based topological data model, then apply modifiable Dijkstra's algorithm to each topological data. Results of ordering analysis about an adjacent space from a target space were visualized and considered ways to take advantage of. Object of this paper is to implement a 3D spatial query for searching a target space with a adjacent relationship in 3D space. And purposes of this study are to 1)generate adjacency based 3D network data via network based topological data model and to 2)implement a 3D spatial query for searching spatial neighborhoods by applying Dijkstra's algorithms to these data.

• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.96-102
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• 2014

In the field of design and manufacturing, there are many problems with managing dynamic states of three-dimensional (3D) objects. In order to solve these problems, the four-dimensional (4D) mesh model and its modeling system have been proposed. The 4D mesh model is defined as a 4D object model that is bounded by tetrahedral cells, and can represent spatio-temporal changes of a 3D object continuously. The 4D mesh model helps to solve dynamic problems of 3D models as geometric problems. However, the construction of the 4D mesh model is limited on the time-series 3D voxel data based method. This method is memory-hogging and requires much computing time. In this research, we propose a new method of constructing the 4D mesh model that derives from the 3D mesh model with continuous rigid body movement. This method is realized by making a swept shape of a 3D mesh model in the fourth dimension and its tetrahedralization. Here, the rigid body movement is a screwed movement, which is a combination of translational and rotational movement.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1093-1099
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• 2022

The number of buildings is increasing day by day. The next logical footstep is tackling challenges regarding scarcity of resources and sustainability, as well as shifting focus on existing building structures to renovate and retrofit. Many existing old and heritage buildings lack documentation, such as building models, despite their necessity. Technological advances allow us to use virtual reality, augmented reality, and mixed reality on mobile platforms in various aspects of the construction industry. For these purposes, having a BIM model or high detail 3D model is not always necessary, as a simpler model can serve the purpose within many mobile platforms. This paper streamlines a framework for generating a lightweight 3D model for mobile platforms. In doing so, we use an existing structure's site survey data for the foundation data, followed by mobile VR implementation. This research conducted a pilot study on an existing building. The study provides a process of swiftly generating a lightweight 3D model of a building with relative accuracy and cost savings.

• ETRI Journal
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• v.45 no.2
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• pp.240-253
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• 2023

Spatial information is geometrical information combined with the properties of an object. In city areas where unmanned aerial vehicle (UAV) usage demand is high, it is necessary to determine the appropriate driving altitude considering the height of buildings for safe driving. In this study, we propose a data-provision method that generates the driving altitude of UAVs with a pseudo-3D building model. The pseudo-3D building model is developed using high-precision spatial information provided by the National Geographic Information Institute. The proposed method generates the driving altitude of the UAV in terms of tile information, including the UAV's starting and arrival points and a straight line between the two points, and provides the data to users. To evaluate the efficacy of the proposed method, UAV driving altitude information was generated using data of 763 551 pseudo-3D buildings in Seoul. Subsequently, the generated driving altitude data of the UAV was verified in AirSim. In addition, the execution time of the proposed method and the calculated driving altitude were analyzed.

• Convergence Security Journal
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• v.8 no.4
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• pp.161-166
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• 2008

This paper proposes a new approach to align 3D data sets by using curvatures of feature surface. We use the Gaussian curvatures and the covariance matrix which imply the physical characteristics of the model to achieve registration of unaligned 3D data sets. First, the physical characteristics of local area are obtained by the Gaussian curvature. And the camera position of 3D range finder system is calculated from by using the projection matrix between 3D data set and 2D image. Then, the physical characteristics of whole area are obtained by the covariance matrix of the model. The corresponding points can be found in the overlapping region with the cross-projection method and it concentrates by removed points of self-occlusion. By the repeatedly the process discussed above, we finally find corrected points of overlapping region and get the optimized registration result.

• Journal of Fashion Business
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• v.20 no.3
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• pp.30-42
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• 2016

The objective of this study was to perform 3D solid modeling from 3D scanned surface images of cotton and silk in order to calculate the thermal heat transfer responses using numerical simulations. Continuing from the previous methodology, which provided 3D surface data for a fabric through optical measurements of the fabric microstructure, a simplified 3D solid model, containing a defined unit cell, pattern unit and fabric structure, was prepared. The loft method was used for 3D solid-model generation, and heat transfer calculations, made for the fabric, were then carried out using the 3D solid model. As a result, comprehensive protocols for 3D solid-model generation were established based on the optical measurements of real fabric samples. This method provides an effective means of using 3D information for building 3D models of actual fabrics and applying the model in numerical simulations. The developed process can be used as the basis for other analogous research areas to investigate the physical characteristics of any fabrics.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.13-18
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• 2005

We explore the structure and usefulness of the 3-D residual plot as a basic tool for dealing with interaction in generalized linear models. If predictors have an interaction effect, the shape obtained by rotating the 3-D residual plot will show its presence. To illustrate the use of this plot as an aid to exploring the interaction, we present an example of a binomial regression model using simulated data.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.208-217
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• 2021

3D-CNN is one of the deep learning techniques for learning time series data. However, these three-dimensional learning can generate many parameters, requiring high performance or having a significant impact on learning speed. We will use these 3D-CNNs to learn hand gesture and find the parameters that showed the highest accuracy, and then analyze how the accuracy of 3D-CNN varies through input data changes without any structural changes in 3D-CNN. First, choose the interval of the input data. This adjusts the ratio of the stop interval to the gesture interval. Secondly, the corresponding interframe mean value is obtained by measuring and normalizing the similarity of images through interclass 2D cross correlation analysis. This experiment demonstrates that changes in input data affect learning accuracy without structural changes in 3D-CNN. In this paper, we proposed two methods for changing input data. Experimental results show that input data can affect the accuracy of the model.