• 한국생활과학회지
• /
• 제21권5호
• /
• pp.975-988
• /
• 2012

Although the pattern development for tight-fitting clothing has been carried out using 3D data on humans, the pattern development using 3D scan data obtained for various postures still remains an interesting subject. In this study, we have developed the 2D pattern using the 3D human body reflecting standing and cycling postures. The 3D scan data of a subject was obtained using Cyberware. 2C-AN program(Triangle simplification and the Runge-Kutta method) was used in the system to reduce the 3D scan data points and to make segmented triangular patches in a plane from 3D data. As results, surface distance and area of each body part of standing and cycling postures were also provided for the future application of the functional clothing construction. The area of center piece on the front (c.front) decreased by $106.45cm^2$(-13.08%) and that of lateral piece(s.back) on the back increased by $144.96cm^2$(18.69%) in the patterns of cycling posture. The girth of neck and waist for the cycling posture increased by 0.88cm (3.92%) and 1.56cm(4.40%) respectively, and the that of thigh decreased by 1.01cm(-2.24%). The differences between the area in the 2D pattern obtained from the 3D scan data and that in the 3D scan surface data for standing and cycling postures were very small($-10.34cm^2$(-0.32%) and $-44.33cm^2$(-1.32%)).

• 한국정보처리학회논문지
• /
• 제7권5호
• /
• pp.1491-1499
• /
• 2000

This paper is designed and implemented the data recovery mechanism for 2-D (2-dimensional) bar code system. The data recovery algorithm used the modified Reed-Solomon algorithm and it is implemented into 2-D bar code system. There are 7 types of 2-D bar code system, which are 21x21, 25x25, 41x41, 73x73, 101x101, 177x177. This paper has been experimented that how many data is saved among several 2-D bar code types and how many data re recovered. In the first experiment, the big size 2-D bar code system has many ECC codeword. Therefore, original data cannot be assigned to 2-D bar code system. In the second experiment, even if 35∼40% loss dta for the 2-D bar code system, the 2-D bar code system could have been recovered to original data.

• 한국CDE학회논문집
• /
• 제10권3호
• /
• pp.179-187
• /
• 2005

The usage of mixed 2D and 3D CAD data of commercial CAD systems is required in the construction practice. Sometimes 3D wireframe model is required by end-users when 2D CAD data is delivered. However, current KOSDIC can not represent 3D CAD data, because it has been developed as a 2D drawing delivery standard. Therefore, this study is to provide exchange and sharing of mixed 2D and 3D CAD data that add 3D wireframe model in the KOSDIC. To achieve this purpose, the authors have investigated the 3D CAD entities of commercial CAD systems, and have analyzed STEP standards providing 3D wireframe model. The result, the authors have extracted 3D CAD common entities based wireframe model which shall be added in the KOSDIC. This study can be beneficial by using the developed data model for heterogeneous CAD systems, and by providing the representation of mixed 2D and 3D CAD data in construction practice such as GIS, piping system, and so forth.

• International Journal of Internet, Broadcasting and Communication
• /
• 제13권2호
• /
• pp.208-217
• /
• 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.

• 지구물리와물리탐사
• /
• 제10권4호
• /
• pp.268-274
• /
• 2007

2차원 측선을 따라 획득한 MT 탐사 자료를 3차원 역산하여 제주도 지전기 구조의 해석을 시도하였다. 이에 앞서 TM 모드 자료와 TE 모드 자료를 각각, 또는 두 모드의 자료를 동시에 이용하여 2차원 역산을 수행하였다. 이 세가지 2차원 역산을 통해 얻은 영상을 3차원 영상과 비교분석하기 위해 측선을 포함하는 3차원 모델을 구성하여 3차원 역산 결과를 도출하였다. 모든 역산 결과에서 전체적으로 동일한 층서구조를 확인할 수 있었으나 3차원 역산에서는 보이지 않는 전기비저항 이상대가 2차원 역산에는 나타난다. 이는 측선 직하부에 있지 않은 3차원 이상체의 영향으로 2차원 역산 결과가 왜곡된 것이라 유추할 수 있다. 역산 영상의 비교 분석 결과 측선 하부에서 제주도의 지전기 구조는 심도 5 km 이내에서는 전체적으로 고비저항.저비저항.고비저항의 3층 수평 층서 구조임을 알 수 있었고, 3차원 역산이 더욱 신뢰성 있는 영상을 보임을 확인하였다.

• 한국생활과학회지
• /
• 제19권3호
• /
• pp.555-563
• /
• 2010

With recent advances in 3D scanning technology, three-dimensional (3D) patternmaking is becoming a powerful way to develop garments pattern. This technology is now applicable to the made to measure (MTM) system of both ordinary and tightly fitting garments. Although the pattern of fitted clothing has been developed using 3D human data, it is still interesting to develop cycling pants by considering while-cycling body posture and fabric elasticity. This study adopted the Garland's triangle simplification method in order to simplify data without distorting the original 3D scan. Next, the Runge-Kutta method (2C-AN program) was used to develop a 2D pattern from the triangular pixels in the 3D scanned data. The 3D scanned data of four male, university students aged from 21 to 25, was obtained using Whole body scanner (Model WB4, Cyberware, Inc., USA). Results showed the average error of measurement was $4.58cm^2$ (0.19%) for area and 0~0.61cm for the length between the 3D body scanned data and the 2D developed pattern data. This is an acceptable range of error for garment manufacture. Additionally, the 2D pattern developed, based on the 3D body scanned data, did not need ease for comfort or ease of movement when cycling. This study thus provides insights into how garment patterns may be developed for ergonomic comfort in certain special environments.

• 한국CDE학회논문집
• /
• 제11권6호
• /
• pp.447-454
• /
• 2006

Although there are many needs to use 3D models in MEMS field, it is not easy to generate 3D models based on MEMS CAD. This is because MEMS CAD is based on 2D and their popular format-GDSII file format- has its own limits and problems. The differences between GDSII file format and 3D CAD system, such as (1) superposed modeling, (2) duplicated entity, (3) restricted of entity type, give rise to several problems in data exchange. These limits and problems in GDSII file format have prevented 3D CAD system from generating 3D models from the MEMS CAD. To remove these limits and solve problems, it is important to extract the silhouette of data in the MEMS CAD. The proposed method has two main processes to extract silhouette; one is to extract the pseudo-silhouette from the original 2D MEMS data and the other is to remove useless objects to complete the silhouette. The paper reports on the experience gained in data exchange between 2D MEMS data and 3D models by the proposed method and a case study is presented, which employs the proposed method using MEMS CAD IntelliMask and Solidworks.

• 한국통신학회논문지
• /
• 제37A권10호
• /
• pp.815-820
• /
• 2012

본 논문에서는 홀로그래픽 저장장치를 위한 2차원 검출기인 2차원 SOVA와 반복 검출 2차원 SOVA의 검출 성능을 비교하였다. 홀로그래픽 저장장치는 2차원 인접심볼간 간섭이 있는 채널을 가지고 있어서 2차원 검출기를 사용하여야 검출 성능이 좋다. 2차원 SOVA와 반복 검출 2차원 SOVA는 2차원 인접심볼간 간섭이 있는 채널에서 잘 동작하는 검출기이다. 이 두가지 검출기를 분석하고 성능을 비교해 보았다. 2차원 SOVA는 1차원 검출기에 비해 약 2 dB의 성능이득이 있었고, 반복 검출 2차원 SOVA는 2차원 SOVA에 비해 약 1 dB 정도의 성능 이득이 있었다. 반대로, 반복 검출 2차원 SOVA는 2차원 SOVA에 비해 약 2배 정도 복잡도가 늘어나며, 2차원 SOVA도 1차원 검출기에 비해 약 2배 정도 복잡도가 늘어난다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권4호
• /
• pp.2042-2059
• /
• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.

• 대한공간정보학회지
• /
• 제18권2호
• /
• pp.113-118
• /
• 2010

지형정보에 대한 3차원 복원 및 지리정보에 관한 연구와 적용은 최근 국가적인 정책을 통하여 R&D 사업 및 시범 사업 등으로 여러 분야에 걸쳐 진행되고 있다. LiDAR 시스템은 3차원 공간데이터를 손쉽고 조밀하게 취득할 수 있는 이점이 있어 다방면으로 연구와 활용이 이루어지고 있으나 3차원으로 구성된 점 자료의 특성으로 볼 때 화면을 통한 2차원의 형태로 나타내기 위해서는 많은 연산 처리를 필요로 하게 되어 높은 사양의 처리 프로세서가 필요하다. 이에 비해 2차원 격자구조는 간단한 구조와 처리속도로 인하여 벡터구조에 비하여 저가의 장비에서도 가능한 장점이 있다. 따라서 본 연구에서는 3차원의 형식으로 저장된 LiDAR 자료를 도심지역의 3차원 지형 표현이나 건물 표현등에 활용하고자 할 경우 발생할 수 있는 과대한 저장공간의 요구에 따른 문제를 해소하기 위하여 3차원 지형 표현 자료로 제공하기 유용한 2차원 격자 형태의 자료로 재구성하여 그 저장공간을 축소시키면서 트리구조를 응용하여 세밀한 표현도 가능하도록 하는 저장하는 기법을 제시하고자 한다.