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Computational Symmetry

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Synonyms

Symmetry-based X; Symmetry detection

Definition

Computational symmetry is a branch of research using computers to model, analyze, synthesize, and manipulate symmetries in digital forms, imagery, or otherwise [1].

Background

Symmetry is a pervasive phenomenon presenting itself in all forms and scales, from galaxies to microscopic biological structures, in nature and man-made environments. Much of one’s understanding of the world is based on the perception and recognition of recurring patterns that are generalized by the mathematical concept of symmetries [24]. Humans and animals have an innate ability to perceive and take advantage of symmetry in everyday life [58], while harnessing this powerful insight for machine intelligence remains a challenging task for computer scientists.

Interested readers can find several influential symmetry-related papers below to gain a historic perspective: the wonderful exposition on the role of symmetry in “Biological Shape and Visual Science”...

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References

  1. Liu Y (2002) Computational symmetry. In: Hargittai I, Laurent T (eds) Symmetry 2000. Wenner-Gren international series, vol 80. Portland, London, pp 231–245. ISBN:I 85578 149 2

    Google Scholar 

  2. Weyl H (1952) Symmetry. Princeton University Press, Princeton

    MATH  Google Scholar 

  3. Coxeter H, Moser W (1980) Generators and relations for discrete groups, 4th edn. Springer, New York

    Book  Google Scholar 

  4. Conway J, Burgiel H, Goodman-Strauss C (2008) The symmetries of things. AK Peters, Wellesley

    MATH  Google Scholar 

  5. Thompson DW (1961) On growth and form. Cambridge University Press, Cambridge

    Google Scholar 

  6. Giurfa M, Eichmann B, Menzel R (1996) Symmetry perception in an insect. Nature 382(6590):458–461

    Article  Google Scholar 

  7. Rodríguez I, Gumbert A, Hempel de Ibarra N, Kunze J, Giurfa M (2004) Symmetry is in the eye of the ‘beeholder’: innate preference for bilateral symmetry in flower-naïve bumblebees. Naturwissenschaften 91(8):374–377

    Google Scholar 

  8. Tyler C (ed) (1996) Human symmetry perception and its computational analysis. VSP, Utrecht

    MATH  Google Scholar 

  9. Blum H (1973) Biological shape and visual science (part i). J Theor Biol 38:205–287

    Article  Google Scholar 

  10. Nevatia R, Binford T (1977) Description and recognition of curved objects. Artif Intell 8(1):77–98

    Article  MATH  Google Scholar 

  11. Davis L (1977) Understanding shape: angles and sides. IEEE Trans Comput 26(3):236–242

    Article  MATH  Google Scholar 

  12. Blumenthal AF, Davis L, Rosenfeld A (1977) Detecting natural “plateaus” in one-dimensional patterns. IEEE Trans Comput 26(2):178–179

    Article  Google Scholar 

  13. Kanade T (1981) Recovery of the 3-dimensional shape of an object from a single view. Artif Intell 17:75–116

    Article  Google Scholar 

  14. Brady M, Asada H (1984) Smoothed local symmetries and their implementation. Int J Robot Res 3(3):36–61

    Article  Google Scholar 

  15. Biederman I (1985) Human image understanding: recent research and a theory. Comput Vis Graph Image Process 32:29–73

    Article  Google Scholar 

  16. Pentland A (1986) Perceptual organization and the representation of natural form. Artif Intell 28:293–331

    Article  MathSciNet  Google Scholar 

  17. Lowe D (1985) Perceptual organization and visual recognition. Kluwer Academic, Boston

    Book  Google Scholar 

  18. Terzopoulos D, Witkin A, Kass M (1987) Symmetry-seeking models and 3D object reconstruction. Int J Comput Vis 1:211–221

    Article  Google Scholar 

  19. Liu Y, Hel-Or H, Kaplan C, Van Gool L (2010) Computational symmetry in computer vision and computer graphics: a survey. Found Trends Comput Graph Vis 5(1/2):1–165

    MATH  Google Scholar 

  20. Greenberg MJ (1993) Euclidean and Non-Euclidean geometries: development and history, 3rd edn. WH Freeman, New York

    Google Scholar 

  21. Arnheim R (2004) Art and visual perception: a psychology of the creative eye. University of California Press, Berkeley/London

    Google Scholar 

  22. Coxeter H (1980) Introduction to geometry, 2nd edn. Wiley, New York

    Google Scholar 

  23. Grünbaum B, Shephard G (1987) Tilings and patterns. WH Freeman, New York

    MATH  Google Scholar 

  24. Liu Y (1990) Symmetry groups in robotic assembly planning. PhD thesis, University of Massachusetts, Amherst

    Google Scholar 

  25. Fedorov E (1885) The elements of the study of figures. (Russian) (2) 21. Zapiski Imperatorskogo S. Peterburgskogo Mineralogichesgo Obshchestva (Proc. S. Peterb. Mineral. Soc.). 1–289

    Google Scholar 

  26. Fedorov E (1891) Symmetry of finite figures. (Russian) (2) 28. Zapiski Imperatorskogo S. Peterburgskogo Mineralogichesgo Obshchestva (Proc. S. Peterb. Mineral. Soc.). 1–146

    Google Scholar 

  27. Fedorov E (1891) Symmetry in the plane. (Russian) (2) 28. Zapiski Imperatorskogo S. Peterburgskogo Mineralogichesgo Obshchestva (Proc. S. Peterb. Mineral. Soc.). 345–390

    Google Scholar 

  28. Bieberbach L (1910) Über die Bewegungsgruppen der n-dimensional en Euklidischen Räume mit einem endlichen Fundamental bereich. Göttinger Nachrichten 75–84

    Google Scholar 

  29. Milnor J (1976) Hilbert’s problem 18. In: Proceedings of symposia in pure mathematics, vol 28. American Mathematical Society, Providence. ISBN:0-8218-1428-1 (Browder FE, Mathematical developments arising from Hilbert problems)

    Google Scholar 

  30. Henry N, Lonsdale K (eds) (1969) International tables for X-ray crystallography. Symmetry groups, vol 1. The Kynoch, England/The International Union of Crystallography, Birmingham

    Google Scholar 

  31. Schattschneider D (1978) The plane symmetry groups: their recognition and notation. Am Math Mon 85:439–450

    Article  MathSciNet  MATH  Google Scholar 

  32. Liu Y, Collins RT (2000) A computational model for repeated pattern perception using frieze and wallpaper groups. In: Computer vision and pattern recognition conference (CVPR’00), Hilton Head, SC. IEEE Computer Society, pp 537–544. http://www.ri.cmu.edu/pubs/pub_3302.html

  33. Liu Y, Collins R, Tsin Y (2004) A computational model for periodic pattern perception based on frieze and wallpaper groups. IEEE Trans Pattern Anal Mach Intell 26(3):354–371

    Article  Google Scholar 

  34. Birkoff G (1932) Aesthetic measure. Harvard University Press, Cambridge

    Google Scholar 

  35. Chen P, Hays J, Lee S, Park M, Liu Y (2007) A quantitative evaluation of symmetry detection algorithms. Technical report PSU-CSE-07011 (also listed as technical report CMU-RI-TR-07-36), The Pennsylvania State University, State College, PA

    Google Scholar 

  36. Park M, Lee S, Chen P, Kashyap S, Butt A, Liu Y (2008) Performance evaluation of state-of-the-art discrete symmetry detection algorithms. In: IEEE conference on computer vision and pattern recognition (CVPR 2008), Anchorage, pp 1–8

    Google Scholar 

  37. Liu Y, Collins RT (2001) Skewed symmetry groups. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition (CVPR’01), Kauai, HI. IEEE Computer Society, pp 872–879. http://www.ri.cmu.edu/pubs/pub_3815.html

  38. Lee S, Liu Y (2010) Skewed rotation symmetry group detection. IEEE Trans Pattern Anal Mach Intell 32(9):1659–1672

    Article  Google Scholar 

  39. Tuytelaars T, Turina A, Van Gool L (2003) Non-combinatorial detection of regular repetitions under perspective skew. IEEE Trans Pattern Anal Mach Intell 25(4):418–432

    Article  Google Scholar 

  40. Hays J, Leordeanu M, Efros A, Liu Y (2006) Discovering texture regularity as a higher-order correspondence problem. In: European conference on computer vision (ECCV’06), Graz, Austria

    Google Scholar 

  41. Park M, Liu Y, Collins R (2008) Deformed lattice detection via mean-shift belief propagation. In: Proceedings of the 10th European conference on computer vision (ECCV’08), Marseille, France

    Google Scholar 

  42. Park M, Brocklehurst K, Collins R, Liu Y (2009) Deformed lattice detection in real-world images using mean-shift belief propagation. IEEE Trans Pattern Anal Mach Intell 31(10):1804–1816

    Article  Google Scholar 

  43. Tsin Y, Liu Y, Ramesh V (2001) Texture replacement in real images. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition (CVPR’01), Kauai. IEEE Computer Society, Los Alamitos, pp 539–544

    Google Scholar 

  44. Liu Y, Collins R, Tsin Y (2002) Gait sequence analysis using frieze patterns. In: Proceedings of the 7th European conference on computer vision (ECCV’02), a longer version can be found as CMU RI tech report 01–38 (2001), Copenhagen, Denmark

    Google Scholar 

  45. Liu Y, Tsin Y (2002) The promise and perils of near-regular texture. In: Texture 2002, Copenhagen, Denmark, in conjunction with European conference on computer vision (ECCV’02), pp 657–671

    Google Scholar 

  46. Liu Y, Lin W (2003) Deformable texture: the irregular-regular-irregular cycle. In: Texture 2003, the 3rd international workshop on texture analysis and synthesis, Nice, France, pp 65–70

    Google Scholar 

  47. Liu Y, Lin W, Hays J (2004) Near-regular texture analysis and manipulation. ACM Trans Graph 23(3):368–376

    Article  Google Scholar 

  48. Liu Y, Tsin Y, Lin W (2005) The promise and perils of near-regular texture. Int J Comput Vis 62(1-2):145–159

    Article  Google Scholar 

  49. Lin W, Liu Y (2006) Tracking dynamic near-regular textures under occlusion and rapid movements. In: Proceedings of the 9th European conference on computer vision (ECCV’06), Graz, Austria, vol 2, pp 44–55

    Google Scholar 

  50. Lin W, Liu Y (2007) A lattice-based mrf model for dynamic near-regular texture tracking. IEEE Trans Pattern Anal Mach Intell 29(5):777–792

    Article  Google Scholar 

  51. Liu Y, Belkina T, Hays H, Lublinerman R (2008) Image de-fencing. In: IEEE computer vision and pattern recognition (CVPR 2008), Anchorage, pp 1–8

    Google Scholar 

  52. Park M, Brocklehurst K, Collins R, Liu Y (2010) Image de-fencing revisited. In: Asian conference on computer vision (ACCV’10), Queenstown. IEEE Computer Society, pp 1–13

    Google Scholar 

  53. Schindler G, Krishnamurthy P, Lublinerman R, Liu Y, Dellaert F (2008) Detecting and matching repeated patterns for automatic geo-tagging in urban environments. In: IEEE computer vision and pattern recognition (CVPR 2008), Anchorage, pp 1–8

    Google Scholar 

  54. Han J, McKenna S, Wang R (2008) Regular texture analysis as statistical model selection. In: ECCV08, Marseille

    Google Scholar 

  55. Korah T, Rasmussen D (2008) Analysis of building textures for reconstructing partially occluded facades. In: European conference on computer vision (ECCV08), Marseille, pp 359–372

    Google Scholar 

  56. Hong W, Yang AY, Ma Y (2004) On symmetry and multiple view geometry: structure, pose and calibration from a single image. Int J Comput Vis 60(3):241–265

    Article  Google Scholar 

  57. Park M, Liu Y, Collins R (2008) Efficient mean shift belief propagation for vision tracking. In: Proceedings of computer vision and pattern recognition conference (CVPR’08), Anchorage. IEEE Computer Society

    Google Scholar 

  58. Park M, Brocklehurst K, Collins R, Liu Y (2010) Translation-symmetry-based perceptual grouping with applications to urban scenes. In: Asian conference on computer vision (ACCV’10), Queenstown. IEEE Computer Society, pp 1–14

    Google Scholar 

  59. Wu C, Frahm JM, Pollefeys M (2010) Detecting large repetitive structures with salient boundaries. In: Daniilidis K, Maragos P, Paragios N (eds) European conference on computer vision (ECCV 2010). Lecture notes in computer science, vol 6312. Springer, Berlin/Heidelberg, pp 142–155. doi:10.1007/978-3-642-15552-9_11

    Chapter  Google Scholar 

  60. Liu J, Liu Y (2010) Multi-target tracking of time-varying spatial patterns. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition (CVPR’10), San Francisco. IEEE Computer Society, pp 1–8

    Google Scholar 

  61. Sun Y, Bhanu B (2009) Symmetry integrated region-based image segmentation. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition (CVPR’08). IEEE Computer Society, Anchorage, Alaska, pp 826–831

    Google Scholar 

  62. Yang A, Rao S, Huang K, Hong W, Ma Y (2003) Geometric segmentation of perspective images based on symmetry groups. In: Proceedings of the 10th IEEE international conference on computer vision (ICCV’03), Nice, vol 2, p 1251

    Google Scholar 

  63. Levinshtein A, Sminchisescu C, Dickinson S (2009) Multiscale symmetric part detection and grouping. In: ICCV, Kyoto

    Book  Google Scholar 

  64. Makadia A, Daniilidis K (2006) Rotation recovery from spherical images without correspondences. IEEE Trans Pattern Anal Mach Intell 28:1170–1175

    Article  Google Scholar 

  65. Tuzel O, Subbarao R, Meer P (2005) Simultaneous multiple 3D motion estimation via mode finding on lie groups. In: Proceedings of the 10th IEEE international conference on computer vision (ICCV’05), Beijing, vol I, pp 18–25

    Google Scholar 

  66. Begelfor E, Werman M (2005) How to put probabilities on homographies. IEEE Trans Pattern Anal Mach Intell 27:1666–1670

    Article  Google Scholar 

  67. Liu Y, Schmidt K, Cohn J, Weaver R (2002) Facial asymmetry quantification for expression invariant human identification. In: International conference on automatic face and gesture recognition (FG’02), Washington, DC

    Google Scholar 

  68. Liu Y, Schmidt K, Cohn J, Mitra S (2003) Facial asymmetry quantification for expression invariant human identification. Comput Vis Image Underst J 91(1/2):138–159

    Article  Google Scholar 

  69. Liu Y, Palmer J (2003) A quantified study of facial asymmetry in 3D faces. In: IEEE international workshop on analysis and modeling of faces and gestures, IEEE, Nice, pp 222–229

    Google Scholar 

  70. Mitra S, Liu Y (2004) Local facial asymmetry for expression classification. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition (CVPR’04). IEEE Computer Society, Washington, DC, pp 889–894. http://www.ri.cmu.edu/pubs/pub_4640.html

  71. Mitra S, Lazar N, Liu Y (2007) Understanding the role of facial asymmetry in human face identification. Stat Comput 17:57–70

    Article  MathSciNet  Google Scholar 

  72. Zabrodsky H, Avnir D (1993) Measuring symmetry in structural chemistry. In: Hargittai I (ed) Advanced molecular structure research, vol 1. JAI, Greenwich

    Google Scholar 

  73. Zabrodsky H, Avnir D (1995) Continuous symmetry measures, iv: chirality. J Am Chem Soc 117:462–473

    Article  Google Scholar 

  74. Avnir D, Katzenelson O, Keinan S, Pinsky M, Pinto Y, Salomon Y, Hel-Or H (1997) The measurement of symmetry and chirality: conceptual aspects. In: Rouvray DH (ed) Concepts in chemistry. Research Studies, Somerset, pp 283–324

    Google Scholar 

  75. Kanis DR, Wong JS, Marks TJ, Ratner M, Zabrodsky H, Keinan S, Avnir D (1995) Continuous symmetry analysis of hyperpolarizabilities. characterization of second order non-linear optical response of distorted benzene. J Phys Chem 99:11061–11066

    Article  Google Scholar 

  76. Yogev-Einot D, Avnir D (2006) The temperature-dependent optical activity of quartz: from le châtelier to chirality measures. Tetrahedron Asymmetry 17:2723–2725

    Article  Google Scholar 

  77. Yogev-Einot D, Avnir D (2004) Pressure and temperature effects on the degree of symmetry and chirality of the molecular building blocks of low quartz. Acta Crystallogr B60:163–173

    Article  Google Scholar 

  78. Keinan S, Avnir D (2000) Quantitative symmetry in structure-activity correlations: the near c2 symmetry of inhibitor/hiv-protease complexes. J Am Chem Soc 122:4378–4384

    Article  Google Scholar 

  79. Alvarez S, Alemany P, Casanova D, Cirera J, Llunell M, Avnir D (2005) Shape maps and polyhedral interconversion paths in transition metal chemistry. Coord Chem Rev 249:1693–1708

    Article  Google Scholar 

  80. Pinsky M, Avnir D (1998) Continuous symmetry measures, v: the classical polyhedra. Inorg Chem 37:5575–5582

    Article  Google Scholar 

  81. Steinberg A, Karni M, Avnir D (2006) Continuous symmetry analysis of NMR chemical shielding anisotropy. Chem Eur J 12:8534–8538

    Article  Google Scholar 

  82. Pinto Y, Fowler P, Mitchell D, Avnir D (1998) Continuous chirality analysis of model stone-wales rearrangements in fullerenes. J Phys Chem 102:5776–5784

    Article  Google Scholar 

  83. Keinan S, Avnir D (2001) Continuous symmetry analysis of tetrahedral/planar distortions: copper chlorides and other AB4 species. Inorg Chem 40:318–323

    Article  Google Scholar 

  84. Liu Y, Dellaert F (1998) A classification-based similarity metric for 3D image retrieval. In: Proceedings of computer vision and pattern recognition conference (CVPR’98), Santa Barbara. IEEE Computer Society, pp 800–807

    Google Scholar 

  85. Liu Y, Collins R, Rothfus W (2001) Robust midsagittal plane extraction from normal and pathological 3D neuroradiology images. IEEE Trans Med Imaging 20(3):175–192

    Article  Google Scholar 

  86. Liu Y, Dellaert F, Rothfus W, Moore A, Schneider J, Kanade T (2001) Classification-driven pathological neuroimage retrieval using statistical asymmetry measures. In: International conference on medical imaging computing and computer assisted intervention (MICCAI 2001), Utrecht. Springer, pp 655–665

    Google Scholar 

  87. Liu Y, Teverovskiy L, Carmichael O, Kikinis R, Shenton M, Carter C, Stenger V, Davis S, Aizenstein H, Becker J, Lopez O, Meltzer C (2004) Discriminative MR image feature analysis for automatic schizophrenia and alzheimer’s disease classification. In: 7th international conference on medical imaging computing and computer assisted intervention (MICCAI 2004), Saint-Malo. Springer, pp 378–385

    Google Scholar 

  88. Liu Y, Teverovskiy L, Lopez O, Aizenstein H, Becker J, Meltzer C (2007) Discovery of “biomarkers” for Alzheimer’s disease prediction from structural MR images. In: 2002 IEEE international symposium on biomedical imaging: macro to nano, Arlington, pp 1344–1347

    Google Scholar 

  89. Teverovskiy L, Becker J, Lopez O, Liu Y (2008) Quantified brain asymmetry for age estimation of normal and AD/MCI subjects. In: 2008 IEEE international symposium on biomedical imaging: nano to macro, Paris, pp 1509–1512

    Google Scholar 

  90. Chastain E, Liu Y (2007) Quantified symmetry for entorhinal spatial maps. Neurocomputing 70(10–12):1723–1727

    Article  Google Scholar 

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Liu, Y. (2014). Computational Symmetry. In: Ikeuchi, K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_640

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