• Title, Summary, Keyword: grouping of line

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Clothing Silhouette Image Evaluation related to Life Space (생활공간에 따른 의복실루엣이미지 평가)

  • Park, Young-Sil
    • Fashion & Textile Research Journal
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    • v.2 no.3
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    • pp.246-252
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    • 2000
  • The purpose of this study was to analyze the characteristics of the factor structure in Clothing Silhouette Image and the differences of Image Evaluation related to Grouping of Line and Grouping of Body Emphasis using Silhouette Image Factor and Life Space as variables. Clothing Silhouette Image was estimated by the photographs of 9 Life Spaces ${\times}$ 23 Clothing Silhouettes with 15 semantic differentiated by-polar scales. The major finding were : The factor structure of Clothing Silhouette Image were found to include 4 factor dimensions-Capability Evaluation, Function, Activity. It was clear that Silhouette Image were affected by Life Spaces. There were the differences of Image Evaluation related to Grouping of Line and Grouping of Body Emphasis. There were the differences of Life Space Evaluation related to Grouping of Line and Grouping of Body Emphasis. Therefore it is important to considerate Life Space for selecting Clothing Silhouette.

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3-D Reconstruction of Buildings using 3-D Line Grouping for Urban Modeling

  • Jung, Young-Kee
    • Journal of information and communication convergence engineering
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    • v.7 no.1
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    • pp.1-6
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    • 2009
  • In order to obtain a 3-D urban model, an abstraction of the surface model is required. This paper describes works on the 3D reconstruction and modeling by the grouping 3D line segments extracted from the stereo matching of edges, which is derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.

Model Grouping in a Mixed-model Assembly Line (조립생산 시스템에서의 혼합 모델 그룹화)

  • Kim, Yearn-Min;Seo, Yoon-Ho
    • IE interfaces
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    • v.9 no.2
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    • pp.39-45
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    • 1996
  • This paper investigates the problems of grouping N products on an assembly line with an objective of maximizing the option grouping rate. Before developing a mixed model grouping algorithm, simulation studies are committed for developing operating rules and evaluating the layout production systems. A mixed model grouping algorithm is suggested and it is applied to the color selection lane in automobile production system, which reveals a high mixed model grouping rate.

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3D Building Reconstructions for Urban Modeling using Line Junction Features

  • Lee, Kyu-Won
    • Journal of information and communication convergence engineering
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    • v.5 no.1
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    • pp.78-82
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    • 2007
  • This paper propose a building reconstruction method of urban area for a 3D GIS with stereo images. The 3D reconstruction is performed by the grouping 3D line segments extracted from the stereo matching of salient edges which are derived from multiple images. The grouping is achieved by conditions of degrees and distances between lines. Building objects are determined by the junction combinations of the grouped line segments. The proposed algorithm demonstrates effective results of 3D reconstruction of buildings with 2D aerial images.

Image segmentation and line segment extraction for 3-d building reconstruction

  • Ye, Chul-Soo;Kim, Kyoung-Ok;Lee, Jong-Hun;Lee, Kwae-Hi
    • Proceedings of the KSRS Conference
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    • pp.59-64
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    • 2002
  • This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

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Building Roof Reconstruction in Remote Sensing Image using Line Segment Extraction and Grouping (선소의 추출과 그룹화를 이용한 원격탐사영상에서 건물 지붕의 복원)

  • 예철수;전승헌;이호영;이쾌희
    • Korean Journal of Remote Sensing
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    • v.19 no.2
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    • pp.159-169
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    • 2003
  • This paper presents a method for automatic 3-d building reconstruction using high resolution aerial imagery. First, by using edge preserving filtering, noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line segment linking is performed according to direction and length of line segments and the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. Coplanar grouping and pplygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3D building reconstruction.

Hierarchical Grouping of Line Segments for Building Model Generation (건물 형태 발생을 위한 3차원 선소의 계층적 군집화)

  • Han, Ji-Ho;Park, Dong-Chul;Woo, Dong-Min;Jeong, Tai-Kyeong;Lee, Yun-Sik;Min, Soo-Young
    • Journal of IKEEE
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    • v.16 no.2
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    • pp.95-101
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    • 2012
  • A novel approach for the reconstruction of 3D building model from aerial image data is proposed in this paper. In this approach, a Centroid Neural Network (CNN) with a metric of line segments is proposed for connecting low-level linear structures. After the straight lines are extracted from an edge image using the CNN, rectangular boundaries are then found by using an edge-based grouping approach. In order to avoid producing unrealistic building models from grouping lined segments, a hierarchical grouping method is proposed in this paper. The proposed hierarchical grouping method is evaluated with a set of aerial image data in the experiment. The results show that the proposed method can be successfully applied for the reconstruction of 3D building model from satellite images.

Generation of 3D Building Model by Grouping of 3D Line Segments (3차원 선소의 Grouping에 의한 3차원 건물 모델 발생)

  • Kang, Yon-Uk;Woo, Dong-Min
    • Journal of IKEEE
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    • v.10 no.1
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    • pp.40-48
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    • 2006
  • This paper presents a new rooftop surface estimation method from 3D line segments. 3D rooftop surface estimation is based on the hierarchical grouping and initiated by 3D line merging for the disconnected 3D line segments. Merged 3D lines are applied to the detection of rooftop by surface estimating technique. To estimate surfaces we detect L-corner and T-corner points, and find fixed reliable junction points. The hypothesis of the possible rooftop surfaces are estimated as polygonal surfaces by these fixed junction points and building's rooftop models are generated by testing the possible surfaces in terms of assumptions of building surface properties. We carried out experiments by synthetic images on Avenches data set and the experimental results showed that we could reliably build 3D model with 3D surfaces, errors of which came up with 0.4 - 1.3 meter, 2.5 times more accurate than the elevation date from the conventional area-based stereo.

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Line segment grouping method for building roof detection in aerial images (항공영상에서 건물지붕 검출을 위한 선소의 그룹화 기법)

  • Ye, Cheol-Su;Im, Yeong-Jae;Yang, Yeong-Gyu
    • 한국지형공간정보학회:학술대회논문집
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    • pp.133-140
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    • 2002
  • This paper presents a method for line segment grouping used for detection of various building roofs. First, by using edge preserving filtering. noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line linking is performed according to direction and length of line segments and finally the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. The algorithm has been applied to aerial imagery and the results show accurate building roof detection.

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3D Building Reconstruction Using a New Perceptual Grouping Technique

  • Woo, Dong-Min;Nguyen, Quoc-Dat
    • Journal of IKEEE
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    • v.12 no.1
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    • pp.51-58
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    • 2008
  • This paper presents a new method for building detection and reconstruction from aerial images. In our approach, we extract the useful building location information from the generated disparity map to obtain the segmentation of interested objects and thus reduce significantly unnecessary line segment extracted in low level feature extraction step. Hypothesis selection is carried out by using undirected graph in which close cycles represent complete rooftops hypotheses, and hypothesis are finally tested to contruct building model. We test the proposed method with synthetic images generated from Avenches dataset of Ascona aerial images. The experiment result shows that the extracted 3D line segments of the buildings can be efficiently used for the task of building detection and reconstruction from aerial images.

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