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Sparse Patch Coding for 3D Model Retrieval

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MultiMedia Modeling (MMM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8326))

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Abstract

3D shape retrieval is a fundamental task in many domains such as multimedia, graphics, CAD, and amusement. In this paper, we propose a 3D object retrieval approach by effectively utilizing low-level patches with initial semantics of 3D shapes, which are similar as superpixels in images. These patches are first obtained by means of stably over-segmenting 3D shape, and we adopt five representative geometric features such as shape diameter function, average geodesic distance, and heat kernel signature, to characterize these low-level patches. A large number of patches collected from shapes in a dataset are encoded into visual words by virtue of sparse coding, and input query compares with 3D models in the dataset by probability distribution of visual words. Experiments show that the proposed method achieves comparable retrieval performance to state-of-the-art methods.

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References

  1. Liu, Z., Bu, S., Zhou, K., Gao, S., Han, J., Wu, J.: A survey on partial retrieval of 3D shapes. Journal of Computer Science and Technology 28(5), 836–851 (2013)

    Article  Google Scholar 

  2. Wu, H., Zha, H., Luo, T., Wang, X., Ma, S.: Global and local isometry-invariant descriptor for 3D shape comparison and partial matching. In: Proceedings of IEEE Computer Vision and Pattern Recognition, pp. 438–445 (2010)

    Google Scholar 

  3. Bronstein, M.M., Kokkinos, I.: Scale-invariant heat kernel signatures for non-rigid shape recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1704–1711 (2010)

    Google Scholar 

  4. Sipiran, I.: Local features for partial shape matching and retrieval. In: Proceedings of ACM Multimedia, pp. 853–856 (2011)

    Google Scholar 

  5. Knopp, J., Prasad, M., Willems, G., Timofte, R., Van Gool, L.: Hough transform and 3D SURF for robust three dimensional classification. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part VI. LNCS, vol. 6316, pp. 589–602. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  6. Kokkinos, I., Bronstein, M.M., Litman, R., Bronstein, A.M.: Intrinsic shape context descriptors for deformable shapes. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 159–166 (June 2012)

    Google Scholar 

  7. Berretti, S., Bimbo, A.D., Pala, P.: Partial match of 3D faces using facial curves between SIFT keypoints. In: Proceedings of Eurographics Workshop on 3D Object Retrieval, pp. 117–120 (2011)

    Google Scholar 

  8. Bronstein, A.M., Bronstein, M.M., Guibas, L.J., Ovsjanikov, M.: Shape google: geometric words and expressions for invariant shape retrieval. ACM Transactions on Graphics 30(1), 1–20 (2011)

    Article  Google Scholar 

  9. Lavoué, G.: Combination of bag-of-words descriptors for robust partial shape retrieval. The Visual Computer 28(9), 931–942 (2012)

    Article  Google Scholar 

  10. Mademlis, A., Daras, P., Axenopoulos, A., Tzovaras, D., Strintzis, M.G.: Combining topological and geometrical features for global and partial 3-D shape retrieval. IEEE Transactions on Multimedia 10(5), 819–831 (2008)

    Article  Google Scholar 

  11. Biasotti, S., Marini, S., Spagnuolo, M., Falcidieno, B.: Sub-part correspondence by structural descriptors of 3D shapes. Computer-Aided Design 38(9), 1002–1019 (2006)

    Article  Google Scholar 

  12. Shapira, L., Shalom, S., Shamir, A., Cohen-Or, D., Zhang, H.: Contextual part analogies in 3D objects. International Journal of Computer Vision 89(2-3), 309–326 (2010)

    Article  Google Scholar 

  13. Cornea, N.D., Demirci, M.F., Silver, D.E., Shokoufandeh, A.C., Dickinson, S.J., Kantor, P.B.: 3D object retrieval using many-to-many matching of curve skeletons. Proceedings of Shape Modeling International, 366–371 (June 2005)

    Google Scholar 

  14. Liu, Z., Zhou, K., Bu, S., Sun, X.: Geometrically attributed binary tree for 3D shape matching. In: Computer Graphics International Conference (2011)

    Google Scholar 

  15. Gao, Y., Wang, M., Zha, Z., Tian, Q., Dai, Q., Zhang, N.: Less is more: efficient 3D object retrieval with query view selection. IEEE Transactions on Multimedia 11(5), 1007–1018 (2011)

    Article  Google Scholar 

  16. Gao, Y., Dai, Q., Wang, M., Zhang, N.: 3d model retrieval using weighted bipartite graph matching. Signal Processing: Image Communication 26(1), 39–47 (2011)

    Google Scholar 

  17. Gao, Y., Tang, J., Hong, R., Yan, S., Dai, Q., Zhang, N., Chua, T.S.: Camera constraint-free view-based 3D object retrieval. IEEE Transactions on Image Processing 21(4), 2269–2281 (2012)

    Article  MathSciNet  Google Scholar 

  18. Gao, Y., Wang, M., Tao, D., Ji, R., Dai, Q.: 3-D object retrieval and recognition with hypergraph analysis. IEEE Transactions on Image Processing 21(9), 4290–4303 (2012)

    Article  MathSciNet  Google Scholar 

  19. Papadakis, P., Pratikakis, I., Theoharis, T., Perantonis, S.: PANORAMA-a 3D shape descriptor based on panoramic views for unsupervised 3D object retrieval. International Journal of Computer Vision 89(2-3), 177–192 (2010)

    Article  Google Scholar 

  20. Shan, Y., Sawhney, H.S., Matei, B., Kumar, R.: Shapeme histogram projection and matching for partial object recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(4), 568–577 (2006)

    Article  Google Scholar 

  21. Golovinskiy, A., Funkhouser, T.: Randomized cuts for 3D mesh analysis. ACM Transactions on Graphics 27(5) (2008)

    Google Scholar 

  22. Liu, Z., Tang, S., Bu, S., Zhang, H.: New evaluation metrics for mesh segmentation. Computers and Graphics (SMI) 37(6), 553–564 (2013)

    Article  Google Scholar 

  23. Ben-Chen, M., Gotsman, C., Bunin, G.: Conformal flattening by curvature prescription and metric scaling. Computer Graphics Forum (Eurographics) 28(2), 449–458 (2008)

    Article  Google Scholar 

  24. Shapira, L., Shamir, A., Cohen-Or, D.: Consistent mesh partitioning and skeletonisation using the shape diameter function. The Visual Computer 24(4), 249–259 (2008)

    Article  Google Scholar 

  25. Surazhsky, V., Surazhsky, T., Kirsanov, D., Gortler, S.J., Hoppe, H.: Fast exact and approximate geodesics on meshes. ACM Transactions on Graphics 25(4), 553–560 (2005)

    Article  Google Scholar 

  26. Sun, J., Ovsjanikov, M., Guibas, L.J.: A concise and provably informative multi-scale signature based on heat diffusion. Computer Graphics Forum (SGP) 28(5), 1383–1392 (2009)

    Article  Google Scholar 

  27. Bach, F., Mairal, J., Ponce, J., Sapiro, G.: Sparse coding and dictionary learning for image analysis. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (2010)

    Google Scholar 

  28. Ji, R., Yao, H., Liu, W., Sun, X., Tian, Q.: Task-dependent visual-codebook compression. IEEE Transactions on Image Processing 21(4), 2282–2293 (2011)

    MathSciNet  Google Scholar 

  29. Ji, R., Duan, L.Y., Chen, J., Xie, L., Yao, H., Gao, W.: Learning to distribute vocabulary indexing for scalable visual search. IEEE Transactions on Multimedia 15(1), 153–166 (2011)

    Article  Google Scholar 

  30. Lee, H., Battle, A., Raina, R., Ng, A.Y.: Efficient sparse coding algorithms. In: Proceedings of Neural Information Processing Systems, pp. 801–808 (2007)

    Google Scholar 

  31. Tung, T., Schmitt, F.: The augmented multiresolution reeb graph approach for content-based retrieval of 3D shapes. International Journal of Shape Modeling 11(1), 91–120 (2005)

    Article  Google Scholar 

  32. Tung, T., Schmitt, F., Matsuyama, T.: Topology matching for 3D video compression. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)

    Google Scholar 

  33. Zarpalas, D., Daras, P., Axenopoulos, A., Tzovaras, D., Strintzis, M.G.: 3D model search and retrieval using the spherical trace transform. EURASIP Journal on Advances in Signal Processing, Article 23912 (2007)

    Google Scholar 

  34. Chaouch, M., Verroust-Blondet, A.: 3D model retrieval based on depth line descriptor. In: Proceedings of IEEE International Conference on Multimedia and Expo. 599–602 (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Northwestern Polytechnical University, Xi’an, 710072, China

    Zhenbao Liu, Shuhui Bu, Junwei Han & Jun Wu

Authors
  1. Zhenbao Liu
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  2. Shuhui Bu
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  3. Junwei Han
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  4. Jun Wu
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Editor information

Editors and Affiliations

  1. School of Computing, Dublin City University, 9, Dublin, Ireland

    Cathal Gurrin

  2. Fakultät IV für Elektrotechnik und Informatik, Technische Universität Berlin / DAI-Labor, 10587, Berlin, Germany

    Frank Hopfgartner

  3. Department of Information and Computing Sciences, Universiteit Utrecht, 3584, Utrecht, CC, The Netherlands

    Wolfgang Hurst

  4. UiT The Arctic University of Norway, 9019, Tromsø, Norway

    Håvard Johansen

  5. Singapore University of Technology and Design, Singapore

    Hyowon Lee

  6. School of Electrical Engineering, Dublin City University, Ireland

    Noel O’Connor

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© 2014 Springer International Publishing Switzerland

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Liu, Z., Bu, S., Han, J., Wu, J. (2014). Sparse Patch Coding for 3D Model Retrieval. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8326. Springer, Cham. https://doi.org/10.1007/978-3-319-04117-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-04117-9_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04116-2

  • Online ISBN: 978-3-319-04117-9

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