The purpose of this study is to produce virtual models of women aged in their 60s and to implement the virtual clothing with jackets. We referred to 3D images of standard and obese body types from the 8th Size Korea and attempted to create avatars based on their images through the various trials. Final virtual models were made to reflect the appearance of women in their 60s. For the standard body type, a 3D image with average body measurements was selected. Based on numerous trials aimed at turning her image into an avatar, the auto-converted avatar on CLO 3D was slimmer than the woman in the original image, and hence it was not suitable for the virtual model. After blending, we converted the image into an uneditable avatar for which only the joint points could be moved, thereby creating an avatar that was identical to the original image. We also selected an image of an obese woman with a “beer bottle” body shape from the 8th Size Korea. We created an avatar that resembled her shape by also converting it into an uneditable avatar for which only joint points could be moved. To use these avatars in virtual clothing, we removed masks of avatars and made faces, hair styles, and skin tones representing women in their 60s. The moderately-sized classic jackets were smooth on both virtual models and fitted satisfactorily. This study demonstrated the applicability of virtual model production of various body types or ages in special clothing studies.

This paper proposes a novel approach to preserving and disseminating cultural heritage in the metaverse environment made possible by the advancement of digital technology. The metaverse integrates the real and virtual worlds, enabling experiences similar to real-world museums within the metaverse environment. This technology provides users with more immersive and interactive means to explore cultural heritage. This study addresses the methodology for extracting 3D models from public cultural heritage data sources and integrating these models using the Unity engine to develop a metaverse museum environment. Public data refers to data or information generated or managed by public agencies, encompassing various forms such as text, graphics, images, video, audio, and more. By utilizing 3D data provided by the Cultural Heritage Administration, this research aims to construct a metaverse museum, showcasing the process and outcomes. Through this, users can experience and learn about cultural heritage in more diverse and interesting ways. It is expected that the metaverse will increase the possibility of improving access to and preservation of cultural heritage. Future society requires the ability to understand the metaverse and create new content while communicating and interacting in that space.

VR은 사용자가 가상 공간에 완전히 몰입하고 상호 작용할 수 있는 가상 세계이다. 본 연구는 스톱모션 애니 메이션을 VR 애니메이션으로 제작할 시 효과적인 객체 표현 방법에 대한 내용을 제시하고자 한다. 실험 결 과 데이터는 VR 스톱모션 애니메이션 및 일반 스톱모션 애니메이션, VR게임 등 다양한 콘텐츠에 적용이 가 능하다. 3D 오프젝트의 변화되는 형태를 앵글별로 3D 스캔한 후 게임엔진에서 다양하게 활용할 수 있도록 데이터화 한 뒤 콘텐츠에 적용하여 구현한다. 기존 스톱모션 애니메이션에서 느낄 수 있는 수작업 느낌을 살리되 디지털적인 이펙트를 추가적으로 이용할 수 있는 장점이 있다. 기존의 스톱 모션 애니메이터들이 접 근하기 힘든 영역을 작업하는데 필요한 세가지 모듈을 구현하여 실험하였다. VR 콘텐츠 제작에서 오브젝트 의 표현과 관련된 분야의 발전에 기여하게 될 것이며 새로운 방향을 제시할 것이다. 향후 연구에서는 각 캐 릭터 관절의 움직임에 따른 3D 스캔 데이터 관련 연구를 수행할 예정이다.

PURPOSES : The purpose of this study is to contribute to the utilization of standards while considering the possible upgrade of a local system as a subject of the application. Therefore, this study aims to explore the possible application of LandInfra for a local road management (maintenance) system in the context of enabling the basis of 3D geospatial road information management in Korea. METHODS : Based on a review of related literature and international standards, an analysis of the current system is performed. After reviewing the LandInfra standard, an examination of corresponding classes between each data model (HMS and LandInfra) is performed for the mapping process. After the mapping process, a data model of the LandInfra-based HMS pavement data model is proposed. RESULTS : To apply the LandInfa to the HMS pavement part, an examination of each data model is performed. After this procedure, a LandInfra-based HMS pavement database schema is proposed in the context of enabling 3D geospatial road information management and maintenance, particularly for pavement management information. CONCLUSIONS : This paper presents how the LandInfra international open geospatial standard can be applied to the local road management system (HMS pavement part). As a result of this study, the LandInfra standard could be applied to the HMS; however, an encoding of the standard is required for conformance. Thus, further studies would be the encoding of the proposed data model for conformance with InfaGML encoding standards. In addition, a system prototype may be needed for complete application.

국내에는 독자적으로 연구가 수행되어 개인적으로 보관 중인 지질 연구 자료가 다량 존재하는데, 이 자료에 대한 접근성이 떨어지기 때문에 다른 연구자들과의 공유가 용이하지 않다. 이런 자료에 대한 메타데이터를 체계적으로 구축하고 총괄적으로 관리하여 이 자료를 필요로 하는 연구자들이 효과적으로 연구를 수행할 수 있는 기회를 제공하는 것이 이 연구의 목적이다. 국내에서 연구된 약 1000여개의 지질 시료(900여개의 암석과 화석 시료, 100여개의 박편 시 료)를 수집하였고, 각 시료의 고화질 사진, 분류, 시료명, 보유기관, 산지, 좌표, 특징 등에 대한 메타데이터를 구축하였다. 암석과 화석 시료 100개에 대해 추가적으로 3D 모델링을 수행하였다. 이 연구를 통해 유실되거나 방치되는 중요한 지질 자료에 대한 연구자들의 접근성이 높아지고 자료의 공유가 가능해진다. 따라서 연구자들은 반복적인 연구 자료 수 집 작업으로 인한 시간과 비용의 낭비를 줄일 수 있고, 효율적인 연구를 수행하여 경쟁력을 갖춘 연구 결과를 획득할 수 있다. 또한 이미 확보된 시료에 대한 무분별한 반복 채집으로 인해 중요한, 그리고 피해에 취약한 자료가 훼손되는 것을 방지할 수 있다. 향후 전국의 대학과 연구기관에서 보관중인 다양한 암석과 박편 시료에 대한 메타데이터를 추가로 구축하면 자료의 식별 및 진전된 연구가 가능하고, 더불어 전문적인 광물학 및 암석학의 기초 지식에 대한 비교와 분석을 기대할 수 있다.

The purpose of this study was to make a pants pattern suitable for women 70 to 85 years of age, then analyze that- pattern’s shape, size, appearance, fit, allowance and air gap. Participants made the pattern using 3D simulation program DC Suite version 5.1. The results suggest a design method suitable for the lower-body shapes of elderly women. In external appearance, the A-type earned the highest evaluation in all items except the allowance of the back waist and back hip. The L type earned the highest evaluation in the allowance of back waist and hips. The A-type’s, back waist appeared set at an angle that did not match the body shape of an old-old aged woman in the center-back-line setting. Therefore, the pattern method of A-type combined with L-type’s method of center back, produces an excellent pants pattern. Evaluation of the air gaps among patterns revealed that; the A-type showed the largest air gap in waist and hip circumference and the smallest air gap in thigh circumference. The waists, abdomen, and hip circumferences of older women often become larger while their legs become slimmer. This study accounted for those factors in determining a pattern suitable for the lower-body shape of old-old aged women. However, participants only analyzed four patterns and compared them with women 70 to 85, years of age. Therefore, it is necessary to develop industrial patterns applicable to a wide age group.

In this study, a novel method based on ground penetration radar (GPR) is proposed to categorize underground objects by using both B-scan and C-scan images. Three-dimensional GPR data obtained from a multichannel GPR system are reconstructed into a two-dimensional (2D) grid image which consists of several B-scan and C-scan images. Three-dimensional shape information of an underground object can be well represented in 2D grid image. The 2D grid images are then trained using deep convolutional neural networks (CNN) that is a state-of-the-art technique for image classification problem. The proposed method is validated through field applications on urban roads in Seoul, South Korea.

This paper presents the novel observation model, called Modified Spherical Signature Descriptor(MSSD), capable of representing 2D image generated from 3D point cloud data. The Modified Spherical Signature Descriptor has a uniform mesh grid to accumulate the occupancy evidence caused by neighbor point cloud data. According to a kind of area such as wall, road, tree, car, and so on, the evidence pattern of 2D image looks so different each other. For the parameter learning of Convolutional Neural Network(CNN) layers, these 2D images were applied as the input layer. The Convolutional Neural Network, one of the deep learning methods and familiar with the image analysis, was utilized for the urban structure classification. The case study on CNN practice was introduced in detail in this paper. The simulation results shows that the classification accuracy of CNN with 2D images of the proposed MSSD was improved more than the traditional methods' one.

The apparel industry has recently been recognizing the important target market of middle-aged women. The aim of this study was to examine the anthropometric characteristics of US women of 46 to 65 years of age and identify distinctive body shape characteristics of US middle-aged women. A total of 1915 middle-aged women whose ages ranged from 46 to 65 were selected from the SizeUSA database. The age range was divided into two groups: 46-55 and 56-65. Twenty-four body measurements important for apparel development were chosen. Four factors—Girth Factor, Height Factor, Hip Drop Factor, and Bust Drop Factor—accounted for the US middle-aged women’s body measurements. The body shapes were classified into four body shapes, which were Y-Shape in the overweight range, S-Shape in the overweight range, H-Shape in the overweight range, and the A-Shape in obese range. H-Shape, which was the least-defined waist in relation to the bust and hips with a short height, existed more in older middle-aged women than in younger middle-aged women. Y-Shape, S-Shape, and A-Shape existed more in the group of younger middle-aged women than in the group of older middle-aged women. In addition, compared with the younger middle-aged women, older middle-aged women had narrower shoulders, a larger waist, thinner legs, and a longer distance between side neck to bust point. The findings from the current study may be applied in the apparel industry for developing clothing sizing systems for US middle-aged women.

Measuring body size with a 3D scanner can reduce inter-measurer variability and provide better accuracy compared to using a traditional methods of measurement (Park, Nam, & Park, 2009). Many size measurement projects (or studies) that measure body size established a size measurement method prior to the development of a 3D scanner and automatic size measurement programs that produce 3D virtual body size measurements (Park, &Nam, 2012). Size data measured through an automatic size measurement program are more accurate and have a lower variability that is more appropriate for body measurements (Han, & Nam, 2004; Nam, Choi, Jung, & Yun, 2004). However, this method is limited to healthy subjects who can maintain a correct posture in a 3D scanner. It is difficult for the elderly to maintain the correct posture for body measurements in ‘Basic Human Body Measurements for Technological Design’ of ISO 7250(1997). Body measurement definitions are based on vertical and horizontal directions consequently, it is hard to measure those with a bent body type even if they stand in a correct posture. Most body measurement items are automatically measured in vertical and horizontal directions because current automatic size measurement programs utilize algorithms based on typical body measurement definitions. The size measurement method based on a vertical and horizontal directions tends to have a problem for elderly individuals with a bent body type who have difficulty maintaining a correct posture for 3D scanning as defined in ISO 7250(1997)(Ashdown, & Na, 2008).This study analyzes the problem of present auto-measurement programs that use elderly’s 3D body scan data. We conducted a comparative analysis of elderly’s body sizes using an auto-measurement program from virtual 3D body scan data and direct measurement with traditional measurement methods. We establish 34 typical body size measurements for the use of data from 464 males and 472 females (total 936) between the ages of 70 to 85. For error analysis, data separated to normal values and outliers compared with ISO 20655(2003). ISO 20685 defines the accuracy of extracted measurements by classification and measurement type (segment lengths, body height/breaths/depth, large/small circumferences, and head/hand/foot dimensions). The majority of outliers for the male and female body height type was “height”. Total number of persons with outliers for Height’s data was 603; consequently, 64.4% of subjects (elderly group of 70-85 yrs.) could not maintain a correct posture when scanning. Other data also had many errors from inaccurate measurement postures. A total of 72.3% of males and 70% of females have incorrect values in small circumferences. The segment lengths’ error data was 76.5% of males and 75% of females; in addition, the head dimension’ outliers were 87% for both male and female subjects. Especially 57.46% of males had incorrect data, while 74.67% of females had a type of large circumference. Female chest circumference had significant errors due to sagging breasts. The differences identify with a correlation between type of large circumference (chest, hip, under bust, waist, waist of omphalion) and gender. There were several correlations between the many measurement errors because values over 70% of data have outliers; however, each measurement type has properties in regards to correlation. A substantial positive correlation was found between all measurements (except hip circumference) in the type of large circumference; in addition, one-way ANOVA indicated that the measurements influenced height and were statistically significant. Outliers found in height data for the elderly’s were more likely to have errors in the type of large circumference. The type of body height indicated a strong correlation and statistical significance between the axilla height and other measurements (height, waist, crotch, lateral malleolus). Axilla height with more outliers indicated that other type of body height measurements had a higher potential for errors. The posture for body measurement was standardized as standing erect; however, this study indicated that many measurement errors were possible between using an auto-measurement program and direct measurement. The value of outlier about a particular measurement item can expect increased errors about any group (height: large circumference group/ axilla height: body height group). We have to study the relation in measurements in these types ‘large circumference’ because ‘head dimensions’ types correlate between measurements in each group. We need a more detailed analysis about outliers to find the major factors for measurement errors in regards to the elderly as well as discuss the possibility of ISO measurement-standard’s application for the elderly.

캐릭터 애니메이션 생성을 위해서는 대용량의 기하 모델 데이터와 모션 데이터 처리를 요구한다. 본 연구에서는 이러한 캐릭터 애니메이션 데이터를 다기종 컴퓨터 환경에서 교환하여 사용할 수 있는 방법에 대해서 기술한다. 캐릭터는 일반 그래픽스 도구를 이용하여 H-Anim ISO/IEC JTC1 SC24 표준화 그룹과 Web3D Consortium에 의해 제정된 국제표준인 H-Anim 기반에서 새로 확장된 구조로 제작한다. H-Anim은 현재 인간형 캐릭터 구조의 전송이나 저장에 필요한 계층적 데이터 구조를 X3D 기반으로 정의하고 있으나 캐릭터의 움직임 표현이나 전송을 위한 애니메이션 데이터에 대해서는 정의되어 있지 않다. 본 연구에서는 H-Anim 표준에 애니메이션에 필요한 추가적인 기능을 새로 제공하여 캐릭터 애니메이션 데이터가 호환성을 가질 수 있도록 데이터 형식을 정의하고, 이 때 H-Anim 구조를 만족시키도록 해주기 위한 캐릭터 모델링의 조건과 제작 방법을 설명한다.

This research aims at developing the dress form for the aged women based on their body shapes using the three-dimensional body scan data with the body shape categorization(according to the previous research). To accomplish this goal, the sample group of representative body shape of the 50% of median was selected by using the high frequency proportion range of each type of body shape of the aged women, and the sample group of representative body shape of each type was averaged in a three-dimensional way by using the morphing method of a three-dimension reverse-engineered software. RP in the form of torso was produced based on the shape data of the final model and the data was formed into an actual object, by which an aged women’s dress form model was drawn out. The differences of the girth of the bust, hip and waist between the developed dress form model and the existing dress form model were examined. The result showed that the developed dress form had a bigger size of waist girth than that of bust and hip girth, compared to the existing dress form, which shows that it reflects the aged women’s tendency of abdomen obesity, so it’s expected to be more proper for the human bodies of the targeted age group than the existing dress form. These research results may help design the clothing suitable for the body shape of the aged women so that their demand for the clothing of good fit will be satisfied in the future.

The purpose of this study is to classify body shapes of aged women by using 3D body scan data. For the body shape analysis and classification, 3D body scan data of 270 aged women were used, and 16 main measurements consisting of a human body were used to conduct factor analysis, cluster analysis and discriminant analysis. The analysis were performed on all ‘the method using the absolute value’, ‘the method using index of height and weight’, and ‘the method using index of height,’ and according to the classification results, the method which categorizes body shapes best in terms of their shapes was adopted. As the factor analysis result using the numerical value of height to categorize the body shapes of the aged women, factor 1 was the thickness and width for the height, factor 2 was the height of the upper part of the body for the height, factor 3 was the height of hips for the height, and factor 4 was the height of belly for the height. When the body shapes were categorized with the deducted factors as variables, they were divided into two types. Type 1 was a short and fat body shape(▅ type) and 55.6% of the subjects were of this type. Type 2 was for the body shape whose vertical height, including weight, was long but all kinds of width and thickness were small, that is, tall and thin body shape(▋ type), and 44.4% of the aged women were in this case.

물리탐사와 시추자료에 대해 지구통계학적 복합해석 기술을 적용하여 3차원의 암반등급 해석을 수행하였다. 자료 복합 해석을 위한 다양한 지구통계학적 기술 중에서, 본 연구에서는 물리탐사 자료의 값을 추정하고자 하는 지점의 암반등급의 평균치로 치환하는 국소 변이 평균에 의한 단순 크리깅 기술(Simple Kriging with local varying means)을 사용하였다. 암석의 전기비저항 값은 RMR(Rock Mass Rating)값과 양의 상관관계를 갖는 것으로 알려져 있으나 상관 관계 만에 의한 대응방식은 그 양상이 매우 복잡하고 공간적으로 연관되어 있는 경우가 많아 단순히 적용하기 어려운 경우가 많다. 본 연구에서는 전기비저항과 RMR의 일반적 선형 상관관계 외에 지시자 변환(indicator transform)에 의한 비선형 상관관계를 유도하는 방식을 제안하였다. 또한 본 연구에서는 선형 및 비선형 상관관계에 의해 대응된 비저항 값이 실제 RMR과 비교할 때 나타나는 잔차(residual)에 대해 3차원 지구통계학적 분석을 적용하여 이 결과를 상관관계 결과에 추가함으로써 공간적 특성을 반영하는 RMR 평가를 수행할 수 있었다. 사용된 물리탐사 자료는 전기비저항 및 MT(Magnetotelluric) 탐사 자료이며, 총 10공의 시추자료를 통해 획득한 암반등급 값을 이용하였다. 이와 같은 해석은 조사 대상에 대한 광역적 지질조건을 보다 현실적으로 반영하는 암반등급 분포를 만들어내는 것으로 보인다.