Browse > Article
http://dx.doi.org/10.7848/ksgpc.2011.29.5.459

Application of 3D Chain Code for Object Recognition and Analysis  

Park, So-Young (세종대학교 지구정보공학과)
Lee, Dong-Cheon (세종대학교 지구정보공학과)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.29, no.5, 2011 , pp. 459-469 More about this Journal
Abstract
There are various factors for determining object shape, such as size, slope and its direction, curvature, length, surface, angles between lines or planes, distribution of the model key points, and so on. Most of the object description and recognition methods are for the 2D space not for the 3D object space where the objects actually exist. In this study, 3D chain code operator, which is basically extension of 2D chain code, was proposed for object description and analysis in 3D space. Results show that the sequence of the 3D chain codes could be basis of a top-down approach for object recognition and modeling. In addition, the proposed method could be applicable to segment point cloud data such as LiDAR data.
Keywords
Object recognition; 3D chain code; Data segmentation; Shape analysis; Modeling;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 박소영, 이동천 (2011), 3D 체인코드에 의한 형태묘사와분석, 한국측량학회 춘계학술발표회 논문집, 한국측량학회, pp. 135-136.
2 송낙현, 신성웅, 조홍범, 조우석 (2007), LiDAR 데이터를이용한 옥트리 분할 기반의 지붕요소 자동추출, 한국측량학회지, 한국측량학회, 제 25권 제 4호, pp. 327-336.
3 이선근, 이동천, 염재홍, 임새봄, 김계림 (2007), 수치지도등고선의 Model Key Point 추출과 Progressive Sampling에의한 수치지형모델 생성, 한국측량학회지, 한국측량학회, 제 25권 제 6-2호, pp. 645-651.
4 이진형, 이동천 (2010), 항공영상에 의한 라이다 데이터 분할에 기반한 건물 모델링, 한국측량학회지, 한국측량학회, 제 28권 제 1호, pp. 47-56.
5 한창호, 오준석, 최병욱 (2010), 3차원 체인코드와 은닉마르코프 모델을 이용한 권투모션 인식, 제어.로봇.시스템학회논문지, 제어.로봇.시스템학회, 제 16권 제 8호, pp. 756-760.
6 Blake, A. and Troscianko. T. (1990), AI and the Eye, John Wiely & Sons, New York, NY, p. 290.
7 Bribiesca E. (2000), A Chain Code for Representing 3D Curves, Pattern Recognition, Vol 33, pp. 755-765.   DOI   ScienceOn
8 Bribiesca E. (2004), 3D-Curve Representation by Means of a Binary Chain Code, Mathematical and Computer Modelling, 40, pp. 285-295.   DOI   ScienceOn
9 Haralick, R. and Shapiro, L. (1992), Computer and Robot Vision -Volume 1, Addison-Wesley Pub., Reading. MA., pp. 371-452.
10 Lehar, S. (2002) The World in Your Head: A Gestalt View of the Mechanism of Conscious Experience, Taylor & Francis, New York, NY, pp. 52-55.
11 Marr, D. (1980) Vision: A Computational Investigation into the Human Representation and Processing of Visual Information, W.H. Freeman and Company, San Francisco, CA, p. 397.
12 Schenk, T. (1999) Digital Photogrammetry Vol. 1: Background, Fundamentals, Automatic Orientation Procedures, TerraScience, Laurelville, OH, p. 428.
13 Sonka, M., Hlavac, V., and Boyle, R. (1999) Image Processing, Analysis, and Machine Vision, 2nd ed., PWS Publishing, New York, NY, p. 770.
14 Tanimoto, S. (1987) The Elements of Artificial Intelligence: An Introduction Using LISP, Computer Science Press, Rockville, MD, p. 527.
15 Wulandhari, L. and Haron, H. (2008) The Evolution and Trend of Chain Code Scheme. International Congress for Global Science and Technology - Graphics, Vision, and Image Processing, Volume 8, Issue III, pp. 17-23.
16 김성준, 이임평 (2010), 라이다데이터 분할 알고리즘의 시뮬레이션 기반 성능평가, 한국지형공간정보학회지, 한국지형공간정보학회, 제 18권 제 2호, pp. 119-129.