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Evaluation of shape similarity for 3D models

3차원 모델을 위한 형상 유사성 평가

  • 김정식 (세종대학교 대학원 컴퓨터공학과) ;
  • 최수미 (세종대학교 소프트웨어공학과)
  • Published : 2003.10.01

Abstract

Evaluation of shape similarity for 3D models is essential in many areas - medicine, mechanical engineering, molecular biology, etc. Moreover, as 3D models are commonly used on the Web, many researches have been made on the classification and retrieval of 3D models. In this paper, we describe methods for 3D shape representation and major concepts of similarity evaluation, and analyze the key features of recent researches for shape comparison after classifying them into four categories including multi-resolution, topology, 2D image, and statistics based methods. In addition, we evaluated the performance of the reviewed methods by the selected criteria such as uniqueness, robustness, invariance, multi-resolution, efficiency, and comparison scope. Multi-resolution based methods have resulted in decreased computation time for comparison and increased preprocessing time. The methods using geometric and topological information were able to compare more various types of models and were robust to partial shape comparison. 2D image based methods incurred overheads in time and space complexity. Statistics based methods allowed for shape comparison without pose-normalization and showed robustness against affine transformations and noise.

3차원 모델의 형상 유사성 평가는 의학, 기계 공학, 분자 생물학 등의 많은 분야에서 매우 중요하다. 더욱이 3차원 모델이 웹 상에 보편화됨에 따라 3차원 모델들의 분류와 검색에 관한 연구들이 활발하게 이루어지고 있다. 본 논문에서는 3차원 형상 표현 방법들과 유사성 평가에 대한 주요 개념들을 기술하고, 최근의 형상 비교에 관한 연구들을 다해상도, 위상 기하학, 2차원 영상, 통계학 기반 방법들로 분류하여 그 특징들을 분석하였다. 또한 논문에서 채택한 유일성, 강인성, 불변성, 다해상도, 효율성, 비교범위와 같은 기준을 사용하여 그 성능을 비교 평가하였다. 다해상도 기반 방법은 비교를 위한 계산 시간은 감소시킨 반면 전처리 시간은 증가시켰다. 기하 및 위상 정보를 이용한 방법은 보다 다양한 형태의 모델들을 비교할 수 있었고 부분적인 형상 비교에도 강인하였다. 2차원 영상을 이용한 방법들은 시간 및 공간 복잡도가 높게 나타났다. 통계학 기반 방법들은 포즈 정규화 작업 없이 형상 비교가 가능하였고, 어파인 변환 및 잡음에도 강인한 결과를 보였다.

Keywords

References

  1. Helen M. Berman and John Westbrook and Zukang Feng and Gary Gilliland and T. N. Bhat and Helge Weissig and Ilya N. Shindyalov and Philip E. Bourne, 'The Protein Data Bank,' Nucleic Acids Research, 28, pp.235-242, 2000 https://doi.org/10.1093/nar/28.1.235
  2. M. Crudele and G. J. Clapworthy and M. A. Krokos and G. Salcito and N. Vasilonikolidakis, 'A Distributed Database on the INTERNET of 3D Models of Human Pathological Organs,' 10th IEEE Symposium on Computer Based Medical Systems Slovenia 1997, pp.256-260, 1997 https://doi.org/10.1109/CBMS.1997.596444
  3. C. Dorai and A. K. Jain, 'COSMOS-A Representation Scheme for 3D Free-Form Objects,' IEEE Trans. PAMI, Vol.19, pp.1115-1130, 1997 https://doi.org/10.1109/34.625113
  4. Longin Jan Latecki and Rolf Lakarnper and Ulrich Eckhardt, 'Shape Descriptors for Non-rigid Shapes with a Single Closed Contour,' IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp.424-429, 2000
  5. Seema Jaggiy and W. Clem Karlz and Stephane G. Mallatx and Alan S. Willsky, 'Silhouette Recognition using High Resolution Pursuit,' journal Pattern Recognition, Vol. 23, No.5, pp.753-771, May, 1999 https://doi.org/10.1016/S0031-3203(98)00112-5
  6. Niblack W. et al., 'QBIC Project: querying images by content, using colour, texture, and shape,' Proceedings of Conference on Storage and Retrieval for Image and Video Databases, 1-3, San Jose, California, US, SPIE Vol.1908, pp.1908-1920, Feb., 1993 https://doi.org/10.1117/12.143648
  7. Chen, G. and T. D. Bui, 'Invariant Fourier-wavelet descriptor for pattern recognition,' Pattern Recognition, Vol. 32, No.7, pp.1083-1088, 1999. https://doi.org/10.1016/S0031-3203(98)00148-4
  8. Zhang, D. and Lu, G., 'Shape-based image retrieval using generic Fourier descriptor,' SP: IC(17), No.10, pp.825-848, November, 2002 https://doi.org/10.1016/S0923-5965(02)00084-X
  9. B. Hom, 'Extended gaussian images,' Proc. of the IEEE, 72(12), pp.1671-1686, December, 1984 https://doi.org/10.1109/PROC.1984.13073
  10. D. Zhang and M. Hebert, 'Harmonic maps and their applications in surface matching,' IEEE Conf. on Computer Vision and Pattern Recognition (CVPR '99), 1999 https://doi.org/10.1109/CVPR.1999.784731
  11. T. Binford, 'Visual perception by computer,' IEEE Conference on Systems Science and Cybernetics, 1971
  12. S. Skiena and W. Smith and P. Lemke, 'Reconstructing sets from interpoint distances,' Proc. of Sixth Annual Symp. on Computational Geometry, pp.332-339, 1990 https://doi.org/10.1145/98524.98598
  13. E. Bardinet and S. F. Vidal and S. D. Arroyo and G. Malandain and N. P. de la Blanca Capilla, 'Structural object matching,' Technical Report DECSAI-000303, Dept. of Computer Science and AI, University of Granada, Spain, February, 2000
  14. J. Bloomenthal and C. Lim, 'Skeletal methods of shape manipulation,' Shape Modeling and Applications, pp.44-47, 1999 https://doi.org/10.1109/SMA.1999.749322
  15. Masaki Hilaga et al., 'Topology Matching for Fully Automatic Similarity Estimation of 3D Shapes,' The proceeding of SIGGRAPH 2001, pp.203-212, 2001 https://doi.org/10.1145/383259.383282
  16. R. Osada and T. Funkhouser and B. Chazelle and D. Dobkin, 'Matching 3D Models with Shape Distribution,' Proc. Shape Modeling Int'l, 2001
  17. Remco C. Veltkamp and, Michiel Hagedoorn, 'Shape Similarity Measures, Properties and Constructions,' VISUAL 2000, pp.467-476, 1999
  18. Arthur R. Pope, 'Model-based object recognition: A survey of recent research,' Technical Report TR-94-04, University of British Columbia, January, 1994
  19. Loncaric, S., 'A survey of shape analysis techniques,' Pattern recognition, Vol.31(8), pp.983-1001, 1998 https://doi.org/10.1016/S0031-2023(97)00122-2
  20. Thomas Funkhouser, 'Overview of 3D Object Representations,' Princeton University, COS 526, 2002
  21. L-H. Chen et al., 'Similarity measure for superquadrics,' IEE Proc. Image Signal Process., Vol.l44, No.4, August, 1997 https://doi.org/10.1049/ip-vis:19971303
  22. Christopher M. Cyr and Benjamin B. Kimia, '3D Object Recognition Using Shape Similarity-Based Aspect Graph,' ICCV 2001, pp.254-261, 2001
  23. Grimson, W. E. L., 'Object Recognition by Computer: The Role of Geometric Constraints,' MIT Press, 1990
  24. Christopher M. Cyr and Ahmed F. Kamal and Thomas B. Sebstian and Benjamin B. Kirnja, '2D-3D Registration Based on Shape Matching,' Mathematical Methods of Biomedical Image Analysis (MMBIA), pp.198-203, 2000 https://doi.org/10.1109/MMBIA.2000.852378
  25. M. Teodoro and G. N. Phillips, Jr. and L. Kavraki, 'Molecular Docking : A Problem with Thousands of Degrees of Freedom,' IEEE International Conference on Robotics and Automation (ICRA), Seoul, Korea, pp.960-900, 2001 https://doi.org/10.1109/ROBOT.2001.932674
  26. Esther Arkin and Paul Chew and Daniel Huttenlocher and KIara Kedem and Joseph Mitchel, 'An efficiently corriputable metric for comparing polygonal shapes,' IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(3), pp.209-215, 1991 https://doi.org/10.1109/34.75509
  27. Veltkamp, R. C., 'Shape matching: Similarity measures and algorithms,' In Shape Modelling International (Genova), pp.188-197, 2001 https://doi.org/10.1109/SMA.2001.923389
  28. D. Marr and H. Nishihara, 'Representation and recognition of the spatial organization of three-dimensional shapes,' Proceedings of the Royal Society of London, B200, pp.269-294, 1978
  29. M. Brady, 'Criteria for representations of shape,' In J. Beck, B. Hope, and A. Rosenfeld, editors, Human and Machine Vision, Academic Press, pp.39-84, 1983
  30. Thomas Funkhouser and Patrick Min and Michael Kazhdan and Joyce Chen and Alex Halderman and David Dobkin and David Jacobs, 'A Search Engine for 3D Models,' to appear in ACM Transactions on Graphics, pp. 83-105, January, 2003 https://doi.org/10.1145/588272.588279
  31. I. Kolonias and D. Tzovaras and S. Malassiotis and M. G. Strintzis, 'Content-Based Search of VRML Models Using Shape Descriptors,' Proc. Euroimage ICAV 3D 2001 Conference, Mykonos, Greece, May, 2001 https://doi.org/10.1109/ICIP.2001.958442
  32. D. V. Vranic and D. Saupe, '3D Shape Descriptor Based on 3D Fourier Transform,' In Proceedings of the EURASIP Conference on Digital Signal Processing for Multimedia Communications and Services (ECMCS 2001) (editor K. Fazekas), Budapest, Hungary, pp.271-274, September, 2001
  33. Suzuki, M. T., 'Web-based retrieval system for 3D polygonal models,' Joint Ninth IFSA World Congress and Twentieth NAFIPS International Conference (IFSN NAFIPS 2001), pp.2271-2276, 2001 https://doi.org/10.1109/NAFIPS.2001.944425
  34. Silvia Biasotti, 'Topological techniques for shape understanding,' CESCG 2001, 2001
  35. G. Reeb, 'Sur les points singuliers d'une forme de Pfaff completement integrable ou dune fonction numerique [On the Singular Points of a Completely Integrable Pfaff Form or of a Numerical Function],' Comptes Randus Acad. Sciences Paris, Vol.222, pp.847-849, 1946
  36. Cheuk Yiu Ip and Daniel Lapadat and Leonard Sieger and William C. Regli, 'Using Shape Distributions to Compare Solid Models,' 7th ACM Symposium on Solid Modeling and Applications, Saarbrken, Germany, Jun., 2002
  37. M. Ankerst and G. Kastenmuller and H.-P. Kriegel and T. Seidl, '3D Shape Histograms for Similarity Search and Classification in Spatial Databases,' Symposium on Large Spatial Databases, pp.207-226, 1999