Skip to main content
Log in

Graph-based deformable matching of 3D line with application in protein fitting

  • Original Article
  • Published:
The Visual Computer Aims and scope Submit manuscript

An Erratum to this article was published on 07 July 2015

Abstract

We present an algorithm for matching two sets of line segments in 3D that have undergone non-rigid deformations. This problem is motivated by a biology application that seeks a correspondence between the alpha-helices from two proteins, so that matching helices have similar lengths and these can be aligned by some low-distortion deformation. While matching between two feature sets have been extensively studied, particularly for point features, matching line segments has received little attention so far. As typical in point-matching methods, we formulate a graph matching problem and solve it using continuous relaxation. We make two technical contributions. First, we propose a graph construction for undirected line segments such that the optimal matching between two graphs represents an as-rigid-as-possible deformation between the two sets of segments. Second, we propose a novel heuristic for discretizing the continuous solution in graph matching. Our heuristic can be applied to matching problems (such as ours) that are not amenable to certain heuristics, and it produces better solutions than those applicable heuristics. Our method is compared with a state-of-art method motivated by the same biological application and demonstrates improved accuracy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Abeysinghe, S.S., Baker, M.L., Chiu, W., Ju, T.: Semi-isometric registration of line features for flexible fitting of protein structures. Comput. Graph. Forum 29(7), 2243–2252 (2010)

    Article  Google Scholar 

  2. Anguelov, D., Koller, D., Srinivasan, P., Thrun, S., Pang, H.-C., Davis, J.: The correlated correspondence algorithm for unsupervised registration of nonrigid surfaces. In: Advances in Neural Information Processing Systems (NIPS 2004), Vancouver, Canada (2004)

  3. Baker, M.L., Ju, T., Chiu, W.: Identification of secondary structure elements in intermediate-resolution density maps. Structure 15(1), 7–19 (2007)

    Article  Google Scholar 

  4. Berman, H., Henrick, K., Nakamura, H.: Announcing the worldwide protein data bank. Nat. Struct. Mol. Biol. 10(12), 980–980 (2003)

    Article  Google Scholar 

  5. Chang, W., Zwicker, M.: Range scan registration using reduced deformable models. Comput. Graph. Forum 28(2), 447–456 (2009)

    Article  Google Scholar 

  6. Chertok, M., Keller, Y.: Efficient high order matching. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2205–2215 (2010)

    Article  Google Scholar 

  7. Chiu, W., Baker, M.L., Almo, S.C.: Structural biology of cellular machines. Trends Cell Biol. 16, 144–150 (2006)

    Article  Google Scholar 

  8. Chou, S.-L., Tsai, W.-H.: Line segment matching for 3d computer vision using a new iteration scheme. Mach. Vis. Appl. 6(4), 191–205 (1993)

    Article  Google Scholar 

  9. Cour, v, Srinivasan, P., Shi, J.: Balanced graph matching. In: Schölkopf, B., Platt, J., Hoffman, T. (eds.) Advances in Neural Information Processing Systems 19, pp. 313–320. MIT Press, New York (2007)

    Google Scholar 

  10. Duchenne, O., Bach, F., Kweon, I.-S., Ponce, J.: A tensor-based algorithm for high-order graph matching. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2383–2395 (2011)

    Article  Google Scholar 

  11. Feng, W., Huang, J., Ju, T., Bao, H.: Feature correspondences using morse smale complex. Vis. Comput. 29(1), 53–67 (2013)

    Article  Google Scholar 

  12. Gold, S., Rangarajan, A.: A graduated assignment algorithm for graph matching. Pattern Anal. Mach. Intell. IEEE Trans. 18(4), 377–388 (1996)

    Article  Google Scholar 

  13. Horaud, R.P., Skordas, T.: Stereo correspondence through feature grouping and maximal cliques. IEEE Trans. Pattern Anal. Mach. Intell. 11(11), 1168–1180 (1989)

    Article  Google Scholar 

  14. Kaick, O. V., Zhang, H., Hamarneh, G., Cohen-or, D.: A survey on shape correspondence. Comp. Graph. Forum 30(6), 1681–1707 (2011)

  15. Leordeanu, M., Hebert, M.: A spectral technique for correspondence problems using pairwise constraints. In: Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on, vol. 2, pp. 1482–1489. IEEE (2005)

  16. Leordeanu, M., Hebert, M., Sukthankar, R.: An integer projected fixed point method for graph matching and map inference. In: Advances in Neural Information Processing Systems, pp. 1114–1122 (2009)

  17. Loiola, E.M., de Abreu, N.M.M., Boaventura-Netto, P.O., Hahn, P., Querido, T.: A survey for the quadratic assignment problem. Eur. J. Oper. Res. 176(2), 657–690 (2007)

    Article  MATH  Google Scholar 

  18. Schellewald, C., Schnorr, C.: Probabilistic subgraph matching based on convex relaxation. In: EMMCVPR, vol. 3757 of Lecture Notes in Computer Science, pp. 171–186. Springer, New York (2005)

  19. Tam, G.K., Martin, R.R., Rosin, P.L., Lai, Y.-K.: Diffusion pruning for rapidly and robustly selecting global correspondences using local isometry. ACM Trans. Graph. 33(1), 4 (2014)

    Article  Google Scholar 

  20. Tam, G. K. L., Cheng, Z.-Q., Lai, Y.-K., Langbein, F.C., Liu, Y., Marshall, D., Martin, R.R., Sun, X.-F., Rosin, P.L.: Registration of 3D point clouds and meshes: a survey from rigid to non-rigid. IEEE Trans. Visual. Comp. Graph. 19(7), 1199–1217 (2013)

  21. Tevs, A., Bokeloh, M., Wand, M., Schilling, A., Seidel, H.-P.: Isometric registration of ambiguous and partial data. In: CVPR, pp. 1185–1192. IEEE (2009)

  22. Topf, M., Lasker, K., Webb, B., Wolfson, H., Chiu, W., Sali, A.: Protein structure fitting and refinement guided by cryo-em density. Structure 16(2), 295–307 (2008)

    Article  Google Scholar 

  23. Trabuco, L.G., Villa, E., Mitra, K., Frank, J., Schulten, K.: Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics. Structure 16(5), 673–683 (2008)

    Article  Google Scholar 

  24. Ullmann, J.R.: An algorithm for subgraph isomorphism. J. ACM 23(1), 31–42 (1976)

    Article  MathSciNet  Google Scholar 

  25. van Kaick, O., Hamarneh, G., Zhang, H., Wighton, P.: Contour correspondence via ant colony optimization. In: Alexa, M., Gortler, S. J., Ju, T., (eds.) Pacific Conference on Computer Graphics and Applications, pp. 271–280 (2007)

  26. Wang, L., Neumann, U.: A robust approach for automatic registration of aerial images with untextured aerial lidar data. In: CVPR, pp. 2623–2630. IEEE (2009)

  27. Yu, Z., Bajaj, C.L.: A structure tensor approach for 3d image skeletonization: applications in protein secondary structure analysis. In: ICIP, pp. 2513–2516 (2006)

  28. Zheng, W.: Accurate flexible fitting of high-resolution protein structures into cryo-electron microscopy maps using coarse-grained pseudo-energy minimization. Biophys. J. 100(2), 478–488 (2011)

    Article  Google Scholar 

  29. Zheng, W., Brooks, B.R.: Normal-modes-based prediction of protein conformational changes guided by distance constraints. Biophys. J. 88(5), 3109–3117 (2005)

    Article  Google Scholar 

  30. Zheng, Y., Doermann, D.S.: Robust point matching for nonrigid shapes by preserving local neighborhood structures. IEEE Trans. Pattern Anal. Mach. Intell. 28(4), 643–649 (2006)

    Article  Google Scholar 

Download references

Acknowledgments

The work is supported in part by the NSF grants (DBI-1356388, DBI-1356306) and the NIH grants (5P41GM103832, 2R01GM079429, R21GM100229).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hang Dou.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dou, H., Baker, M.L. & Ju, T. Graph-based deformable matching of 3D line with application in protein fitting. Vis Comput 31, 967–977 (2015). https://doi.org/10.1007/s00371-015-1115-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-015-1115-x

Keywords

Navigation