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      FFD와 로봇 팔을 이용한 3D 가발 형상 제작 시스템

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      https://www.riss.kr/link?id=A105048802

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      다국어 초록 (Multilingual Abstract)

      In this paper, we propose a new method to automatically make 3D wigs by replacing existing manual wig manufacturing system. To obtain the existing 3D head image, there is a method using a laser and an infrared ray. However, since both methods use ligh...

      In this paper, we propose a new method to automatically make 3D wigs by replacing existing manual wig manufacturing system. To obtain the existing 3D head image, there is a method using a laser and an infrared ray. However, since both methods use light, it is difficult to measure the correct head by the hair. In this paper, we propose a contact type measurement method which has no problem in actual head shape processing even when there is hair. The 3D wig making method of this paper first establishes seven representative landmark points for the head shape and creates a standard 3D head shape which is an ideal head shape. Using the robotic arm designed in this paper, 3D position information of five measurement points is extracted and the 3D head of the subject is generated using the FFD(Free Form Deformation) algorithm based on the corresponding data. As a result of the implemented method, there was an error of 1.1 ~ 5.6% compared between actual head and subject. The proposed technique has the advantage of making the customized wig quickly and efficiently by taking only five 3D contact measurement points of the subject.

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      참고문헌 (Reference)

      1 "https://processing.org"

      2 "http://sizekorea.kr/02_data/directData02.asp"

      3 Marc Levoy, "The digital michelangelo project" 1999

      4 Fausto Bernardini, "The Ball-Pivoting Algorithm for Surface Reconstruction" 5 (5): 349-359, 1999

      5 E. Catmull, "Recursively Generated B-Spline Surfaces on Arbitrary Topological Meshes" 10 (10): 350-355, 1978

      6 J. S. Bridle, "Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition, NATO ASI Series F68, Vol. F68" Springer-Verlag 227-236, 1989

      7 L. Cobalt, "Multi-resolution shape deformations for meshes with dynamic vertex connectivity" 19 (19): C249-C260, 2000

      8 Young-Jun Song, "Facial feature analysis for 3D face modeling" 2 (2): 25-29, 2004

      9 Nina Amenta, "A new Voro-noi-based surface reconstruction algorithm" 415-421, 1998

      10 Maneesh Agrawala, "3D painting on scanned surfaces" 145-150, 1995

      1 "https://processing.org"

      2 "http://sizekorea.kr/02_data/directData02.asp"

      3 Marc Levoy, "The digital michelangelo project" 1999

      4 Fausto Bernardini, "The Ball-Pivoting Algorithm for Surface Reconstruction" 5 (5): 349-359, 1999

      5 E. Catmull, "Recursively Generated B-Spline Surfaces on Arbitrary Topological Meshes" 10 (10): 350-355, 1978

      6 J. S. Bridle, "Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition, NATO ASI Series F68, Vol. F68" Springer-Verlag 227-236, 1989

      7 L. Cobalt, "Multi-resolution shape deformations for meshes with dynamic vertex connectivity" 19 (19): C249-C260, 2000

      8 Young-Jun Song, "Facial feature analysis for 3D face modeling" 2 (2): 25-29, 2004

      9 Nina Amenta, "A new Voro-noi-based surface reconstruction algorithm" 415-421, 1998

      10 Maneesh Agrawala, "3D painting on scanned surfaces" 145-150, 1995

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2022 평가예정 재인증평가 신청대상 (재인증)
      2019-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2016-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2012-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2008-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2006-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.45 0.45 0.39
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.38 0.35 0.566 0.16
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