• Title/Summary/Keyword: 3차원 위상학적 데이터 모델

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Validation of Efficient Topological Data Model for 3D Spatial Queries (3차원 공간질의를 위한 효율적인 위상학적 데이터 모델의 검증)

  • Lee, Seok-Ho;Lee, Ji-Yeong
    • Spatial Information Research
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    • v.19 no.1
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    • pp.93-105
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    • 2011
  • In recent years, large and complex three-dimensional building has been constructed by the development of building technology and advanced IT skills, and people have lived there and spent a considerable time so far. Accordingly. in this sophisticatcd three-dimensional space, emergencies services or convenient information services have been in demand. In order to provide these services efficiently, understanding of topological relationships among the complex space should be supported naturally. Not on1y each method of understanding the topological relationships but also its efficiency can be different depending on different topological data models. B-rep based data model is the most widely used for storaging and representing of topological relationships. And from early 2000s, many researches on a network based topological data model have been conducted. The purpose of this study is to verify the efficiency of performance on spatial queries. As a result, Network-based topological data model is more efficient than B-rep based data model for determining the spatial relationship.

3D Adjacency Spatial Query using 3D Topological Network Data Model (3차원 네트워크 기반 위상학적 데이터 모델을 이용한 3차원 인접성 공간질의)

  • Lee, Seok-Ho;Park, Se-Ho;Lee, Ji-Yeong
    • 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.

Simplification of 3D building models for defined by triangles (삼각면으로 정의된 3차원 건물 모델의 단순화)

  • Oh, So-Jung;Lee, Im-Pyeong;Kim, Tae-Hyun
    • Proceedings of the KSRS Conference
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    • 2009.03a
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    • pp.301-304
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    • 2009
  • 3차원 가시화는 3차원 공간정보를 효율적으로 제공하기 위하여 중요하다. 그러나 기존의 3차원 가시화 소프트웨어는 복잡한 다면체 모델들을 삼각면으로 분할하여 저장하여 불필요한 기하정보들을 포함한다. 따라서 본 연구는 불필요한 기하정보가 제거된 건물 모델을 생성하기 위하여 동일한 삼각면들을 병합하여 다각면으로 정의하는 기하학적 단순화를 수행한다. 이를 위하여, 3차원 모델에 포함된 기하학적 오류와 위상학적 오류들이 제거된 삼각면의 속성을 정의한다. 그리고 이웃면 정보를 생성하여 동일면을 병합하고 병합된 면의 경계점들을 정리함으로써 단순화를 수행한다. 제안된 방법의 수행 결과, 삼각면으로 정의된 복잡한 다면체 모델은 다각면으로 정의된 보다 단순한 다면체 모델로 단순화될 수 있었고 동일한 기하학적 정보를 포함하고 있으나 데이터의 크기가 매우 작아 신속하게 가시화를 수행할 수 있었다. 따라서 제안한 방법론은 3차원 건물모델의 가시화 시간을 크게 줄일 것이다.

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Comparative Analysis of 3D Spatial Data Models (3차원 공간정보 데이터 모델 비교 분석)

  • Park, Se-Ho;Lee, Ji-Yeong
    • Spatial Information Research
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    • v.17 no.3
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    • pp.277-285
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    • 2009
  • Each system should have a suitable data model about their purpose for efficiently managing, analyzing, and manipulating data. And the usable range of application is determined by the data model, and suitable data models are being developed for each application. In GIS, diversity spatial data model is being developed too. The accuracy and update of the spatial data would be important for applying efficient application as well as the data modeling is important as constructing the spatial data structure. Therefore, the purposes of this research are to 1)compare domestic spatial data models with oversea spatial data models about their geometry model, topology model and visualizing method of 3D spatial data 2)to compare the features of the data model by analyzing each data structures. We 3)compare and analyze features of each spatial data models via the quantitative analysis of each spatial data models.

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A Watermarking Algorithm of 3D Mesh Model Using Spherical Parameterization (구면 파라미터기법을 이용한 3차원 메쉬 모델의 워더마킹 알고리즘)

  • Cui, Ji-Zhe;Kim, Jong-Weon;Choi, Jong-Uk
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.1
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    • pp.149-159
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    • 2008
  • In this paper, we propose a blind watermarking algorithm of 3d mesh model using spherical parameterization. Spherical parameterization is a useful method which is applicable to 3D data processing. Especially, orthogonal coordinate can not analyse the feature of the vertex coordination of the 3D mesh model, but this is possible to analyse and process. In this paper, the centroid center of the 3D model was set to the origin of the spherical coordinate, the orthogonal coordinate system was transformed to the spherical coordinate system, and then the spherical parameterization was applied. The watermark was embedded via addition/modification of the vertex after the feature analysis of the geometrical information and topological information. This algorithm is robust against to the typical geometrical attacks such as translation, scaling and rotation. It is also robust to the mesh reordering, file format change, mesh simplification, and smoothing. In this case, the this algorithm can extract the watermark information about $90{\sim}98%$ from the attacked model. This means it can be applicable to the game, virtual reality and rapid prototyping fields.

Navigable Space-Relation Model for Indoor Space Analysis (실내 공간 분석을 위한 보행 공간관계 모델)

  • Lee, Seul-Ji;Lee, Ji-Yeong
    • Spatial Information Research
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    • v.19 no.5
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    • pp.75-86
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    • 2011
  • Three-dimensional modeling of cities in the real-world is an essential task for city planning and decision-making. And many three-dimensional city models are being developed with the development of wireless Internet and location-based services that identify the location of users and provide the information increases for consumers. Especially, in case of urban areas of Korea, indoor space modeling as well as outdoor is needed due to the high-rise buildings densities. Also location-based services should be provided through spatial analysis such as the shortest path based on a space model. Many studies of three-dimensional city models are feature models. In a feature model, space is represented by combining primitives, and relationships among spaces are represented only if shared primitives are detected. So relationships between complex three-dimensional objects in space is difficult to be defined through the feature models. In this study, Navigable space-relation model(NSRM) is developed, which is topological data model for efficient representation of spatial relationships between objects based on the network structure.

Finding Isolated Zones through Connectivity Relationship Analysis in Indoor Space (실내공간의 연결성 분석을 통한 고립지역 탐색)

  • Lee, Seul-Ji;Lee, Ji-Yeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.3
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    • pp.229-240
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    • 2012
  • In Korea, u-City has been constructed as IT-based new city with introduction of the ubiquitous concept. However, most currently provided u-services are just monitoring services based on the USN(Ubiquitous Sensor Network) technology, so spatial analysis is insufficient. Especially, buildings have been rapidly constructed and expanded in multi-levels, and people spend a lot of time in indoor space, so indoor spatial analysis is necessary. Therefore, connectivity relationship in indoor space is analyzed using the topological data model. Topological relationships could be redefined due to the dynamic changes of environment in indoor space, and changes could have an effect on analysis results. In this paper, the algorithms of finding isolated zones is developed by analyzing connectivity relationship between space objects in built-environments after changes of environment in indoor space due to specific situation such as fire. And the system that visualizes isolated zones as well as three-dimensional data structure of indoor space is developed to get the analysis result by using the analysis algorithms.

Spatial Analysis to Capture Person Environment Interactions through Spatio-Temporally Extended Topology (시공간적으로 확장된 토폴로지를 이용한 개인 환경간 상호작용 파악 공간 분석)

  • Lee, Byoung-Jae
    • Journal of the Korean Geographical Society
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    • v.47 no.3
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    • pp.426-439
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    • 2012
  • The goal of this study is to propose a new method to capture the qualitative person spatial behavior. Beyond tracking or indexing the change of the location of a person, the changes in the relationships between a person and its environment are considered as the main source for the formal model of this study. Specifically, this paper focuses on the movement behavior of a person near the boundary of a region. To capture the behavior of person near the boundary of regions, a new formal approach for integrating an object's scope of influence is described. Such an object, a spatio-temporally extended point (STEP), is considered here by addressing its scope of influence as potential events or interactions area in conjunction with its location. The formalism presented is based on a topological data model and introduces a 12-intersection model to represent the topological relations between a region and the STEP in 2-dimensional space. From the perspective of STEP concept, a prototype analysis results are provided by using GPS tracking data in real world.

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A Robust Object Detection and Tracking Method using RGB-D Model (RGB-D 모델을 이용한 강건한 객체 탐지 및 추적 방법)

  • Park, Seohee;Chun, Junchul
    • Journal of Internet Computing and Services
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    • v.18 no.4
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    • pp.61-67
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    • 2017
  • Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

Building change detection in high spatial resolution images using deep learning and graph model (딥러닝과 그래프 모델을 활용한 고해상도 영상의 건물 변화탐지)

  • Park, Seula;Song, Ahram
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.3
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    • pp.227-237
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    • 2022
  • The most critical factors for detecting changes in very high-resolution satellite images are building positional inconsistencies and relief displacements caused by satellite side-view. To resolve the above problems, additional processing using a digital elevation model and deep learning approach have been proposed. Unfortunately, these approaches are not sufficiently effective in solving these problems. This study proposed a change detection method that considers both positional and topology information of buildings. Mask R-CNN (Region-based Convolutional Neural Network) was trained on a SpaceNet building detection v2 dataset, and the central points of each building were extracted as building nodes. Then, triangulated irregular network graphs were created on building nodes from temporal images. To extract the area, where there is a structural difference between two graphs, a change index reflecting the similarity of the graphs and differences in the location of building nodes was proposed. Finally, newly changed or deleted buildings were detected by comparing the two graphs. Three pairs of test sites were selected to evaluate the proposed method's effectiveness, and the results showed that changed buildings were detected in the case of side-view satellite images with building positional inconsistencies.