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      반 밀집 정합에 기반한 저가형 3차원 주름 데이터 복원 = A Low Cost 3D Skin Wrinkle Reconstruction System Based on Stereo Semi-Dense Matching

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      https://www.riss.kr/link?id=A103035108

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      다국어 초록 (Multilingual Abstract)

      In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building and other scene. The target is object measurement, the scene depth calculation and 3D data obtained. There are several challenges in our research. First, it is hard to take the full information wrinkle images by cameras because of light influence, skin with non-rigid object and camera performance. We design a particular computer vision system to take winkle images with a long length camera lens. Second, it is difficult to get the dense stereo data because of the hard skin texture image segmentation and corner detection. We focus on semi-dense stereo matching algorithm for the wrinkle depth. Compared with the 3D scanner, our system is much cheaper and compared with the physical modeling based method, our system is more flexible with high performance.
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      In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building a...

      In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building and other scene. The target is object measurement, the scene depth calculation and 3D data obtained. There are several challenges in our research. First, it is hard to take the full information wrinkle images by cameras because of light influence, skin with non-rigid object and camera performance. We design a particular computer vision system to take winkle images with a long length camera lens. Second, it is difficult to get the dense stereo data because of the hard skin texture image segmentation and corner detection. We focus on semi-dense stereo matching algorithm for the wrinkle depth. Compared with the 3D scanner, our system is much cheaper and compared with the physical modeling based method, our system is more flexible with high performance.

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      참고문헌 (Reference)

      1 M. Pollefeys, "Visual Modeling with a Hand-Held Camera" 59 (59): 207-232, 2004

      2 B. K. P. Horn, "The Variational Approach to Shape from Shading" 33 (33): 174-208, 1986

      3 O. G. Cula, "Skin Texture Modeling" 62 (62): 97-119, 2005

      4 R. Zhang, "Shape from shading: a survey" 21 (21): 690-706, 1999

      5 Y. Z. Yu, "Shadow Graphs and 3D Texture Reconstruction" 62 (62): 35-60, 2005

      6 S. I. Choi, "Shadow Compensation in 2D Images for Face Recognition" 40 (40): 2118-2125, 2007

      7 G. Michael, "Multi-View Stereo For Community Photo Collections" 1-8, 2007

      8 G. Pavlidis, "Methods for 3D digitization of Cultural Heritage" 8 : 93-98, 2007

      9 A. Chiuso, "MFm: 3-D Motion and Structure from 2-D Motion Causally Integrated Over Time Implementation" 734-750, 2000

      10 J. Cech, "Efficient Sampling of Disparity Space for Fast and Accurate Matching" 1-8, 2007

      1 M. Pollefeys, "Visual Modeling with a Hand-Held Camera" 59 (59): 207-232, 2004

      2 B. K. P. Horn, "The Variational Approach to Shape from Shading" 33 (33): 174-208, 1986

      3 O. G. Cula, "Skin Texture Modeling" 62 (62): 97-119, 2005

      4 R. Zhang, "Shape from shading: a survey" 21 (21): 690-706, 1999

      5 Y. Z. Yu, "Shadow Graphs and 3D Texture Reconstruction" 62 (62): 35-60, 2005

      6 S. I. Choi, "Shadow Compensation in 2D Images for Face Recognition" 40 (40): 2118-2125, 2007

      7 G. Michael, "Multi-View Stereo For Community Photo Collections" 1-8, 2007

      8 G. Pavlidis, "Methods for 3D digitization of Cultural Heritage" 8 : 93-98, 2007

      9 A. Chiuso, "MFm: 3-D Motion and Structure from 2-D Motion Causally Integrated Over Time Implementation" 734-750, 2000

      10 J. Cech, "Efficient Sampling of Disparity Space for Fast and Accurate Matching" 1-8, 2007

      11 M. Pollefeys, "Detailed Real-Time Urban 3D Reconstruction From Video" 78 (78): 143-167, 2008

      12 O. Veksler, "Dense Features for Semi-Dense Stereo Correspondence" 47 (47): 247-260, 2002

      13 M. Pollefeys, "A Simple and Efficient Rectification Method for General Motion" 496-501, 1999

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      유사연구자 (20) 활용도상위20명

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2027 평가예정 재인증평가 신청대상 (재인증)
      2021-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2018-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2015-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2013-11-05 학술지명변경 외국어명 : Journal of Korean Society for Internet Information -> Journal of Internet Computing and Services KCI등재
      2011-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2006-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2005-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2003-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.55 0.55 0.63
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.64 0.6 0.85 0.03
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