Abstract
This paper presents a 3D shape retrieval algorithm based on the Bag of Words (BoW) paradigm. For a given 3D shape, the proposed approach considers a set of feature points uniformly sampled on the surface and associated with local Fourier descriptors. This descriptor is computed in the neighborhood of each feature point by projecting the geometry onto the eigenvectors of the Laplace–Beltrami operator; it is very informative, robust to connectivity and geometry changes, and also fast to compute. In a preliminary step, a visual dictionary is built by clustering a large set of feature descriptors, then each 3D shape is described by an histogram of occurrences of these visual words, hence discarding any spatial information. A spatially-sensitive algorithm is also presented where the 3D shape is described by an histogram of pairs of visual words. We show that these two approaches are complementary and can be combined to improve the performance and the robustness of the retrieval. The performances have been compared against very recent state-of-the-art methods on several different datasets. For global shape retrieval, our combined approach is comparable to these recent works, however, it clearly outperforms them in the case of partial shape retrieval.
Similar content being viewed by others
References
Agathos, A., Pratikakis, I., Papadakis, P., Perantonis, S., Azariadis, P., Sapidis, N.: Retrieval of 3D articulated objects using a graph-based representation. In: Eurographics Workshop on 3D Object Retrieval (2009)
Ben-Chen, M., Gotsman, C.: Characterizing shape using conformal factors. In: Eurographics Workshop on 3D Object Retrieval (2008)
Bowers, J., Wang, R., Wei, L.y., Maletz, D.: Parallel Poisson disk sampling with spectrum analysis on surfaces. In: SIGGRAPH Asia (2010)
Bronstein, A.M., Bronstein, M.M., Guibas, L.J., Ovsjanikov, M.: Shape Google: geometric words and expressions for invariant shape retrieval. ACM Trans. Graph. 30(1), 1–20 (2011)
Bronstein, A.M., Bronstein, M.M., Kimmel, R., Mahmoudi, M., Sapiro, G.: A Gromov-Hausdorff framework with diffusion geometry for topologically-robust non-rigid shape matching. Int. J. Comput. Vis. 89(2–3), 266–286 (2009)
Chen, D., Tian, X., Shen, Y.T., Ming, O.: On visual similarity based 3D model retrieval. Comput. Graph. Forum 22(3), 223–232 (2003)
Cornea, N., Demirci, M.: 3D object retrieval using many-to-many matching of reconstruction-based curve skeletons. In: Veltkamp, R.C., ter Haar, F.B. (eds.) SHREC2007 3D Shape Retrieval Contest, pp. 50–52 (2007)
Csurka, G., Dance, C., Fan, L., Willamowski, J., Cedric, B.: Visual categorization with bags of keypoints. In: ECCV International Workshop on Statistical Learning in Computer Vision (2004)
Dey, T., Li, K., Luo, C., Ranjan, P., Safa, I., Wang, Y.: Persistent heat signature for pose-oblivious matching of incomplete models. Comput. Graph. Forum 29(5), 1545–1554 (2010)
Fei-Fei, L., Perona, P.: A bayesian hierarchical model for learning natural scene categories. In: Computer Vision and Pattern Recognition, pp. 524–531 (2005)
Ferreira, A., Marini, S., Attene, M., Fonseca, M.J., Spagnuolo, M., Jorge, J.a., Falcidieno, B.: Thesaurus-based 3D object retrieval with part-in-whole matching. Int. J. Comput. Vis. 89(2–3), 327–347 (2009)
Fu, Y., Zhou, B.: Direct sampling on surfaces for high quality remeshing. Comput. Aided Geom. Des. 26(6), 711–723 (2009)
Funkhouser, T., Min, P., Kazhdan, M., Chen, J., Halderman, A., Dobkin, D., Jacobs, D.: A search engine for 3D models. ACM Trans. Graph. 22(1), 83 (2003)
Funkhouser, T., Shilane, P.: Partial matching of 3D shapes with priority-driven search. In: Eurographics Symposium on Geometry Processing, p. 142 (2006)
Gal, R., Shamir, A., Cohen-Or, D.: Pose-oblivious shape signature. IEEE Trans. Vis. Comput. Graph. 13(2), 261–271 (2007)
Itskovich, A., Tal, A.: Surface partial matching & application to archeology. Comput. Graph. Forum 35, 334–341 (2011)
Jain, V., Zhang, H.: A spectral approach to shape-based retrieval of articulated 3D models. Comput. Aided Des. 39(5), 398 (2007)
Järvelin, K., Kekäläinen, J.: Cumulated gain-based evaluation of IR techniques. ACM Trans. Inf. Syst. 20(4), 422 (2002)
Lavoué, G.: Bag of words and local spectral descriptor for 3d partial shape retrieval. In: Eurographics Workshop on 3D Object Retrieval (2011)
Lévy, B., Zhang, H.: Spectral mesh processing. In: Siggraph 2010 Course (2010)
Li, X., Godil, A.: Exploring the Bag-of-Words method for 3D shape retrieval. In: IEEE International Conference on Image Processing, pp. 437–440 (2009)
Lian, Z., Godil, A., Sun, X.: Visual similarity based 3D shape retrieval using bag-of-features. In: Shape Modeling International (2010)
Liu, Y., Zha, H., Qin, H.: Shape topics: a compact representation and new algorithms for 3D partial shape retrieval. In: Computer Vision and Pattern Recognition, pp. 2025–2032 (2006)
Lloyd, S.: Least squares quantization in PCM. IEEE Trans. Inf. Theory 28(2), 129–137 (1982)
Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
Marini, S., Patané, G., Spagnuolo, M., Falcidieno, B.: Feature selection for enhanced spectral shape comparison. In: Eurographics Workshop on 3D Object Retrieval (2010)
Marini, S., Biasotti, S., Spagnuolo, M., Falcidieno, B.: Sub-part correspondence by structural descriptors of 3D shapes. In: Veltkamp, R.C., ter Haar, F.B. (eds.) SHREC2007 3D Shape Retrieval Contest, pp. 53–55 (2007)
Mikolajczyk, K., Schmid, C.: Performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
Ohbuchi, R., Osada, K., Furuya, T., Banno, T.: Others: salient local visual features for shape-based 3D model retrieval. In: Shape Modeling International (2008)
Papadakis, P., Pratikakis, I., Theoharis, T., Passalis, G.: 3D object retrieval using an efficient and compact hybrid shape descriptor. In: Eurographics Workshop on 3D Object Retrieval (2008)
Reuter, M., Wolter, F., Peinecke, N.: Laplace-Beltrami spectra as shape-DNA of surfaces and solids. Comput. Aided Des. 38(4), 342–366 (2006)
Ruggeri, M.R., Patanè, G., Spagnuolo, M., Saupe, D.: Spectral-driven isometry-invariant matching of 3D shapes. Int. J. Comput. Vis. 89(2–3), 248–265 (2009)
Rustamov, R.: Laplace-Beltrami eigenfunctions for deformation invariant shape representation. In: Eurographics Symposium on Geometry Processing, pp. 225–233 (2007)
Shilane, P., Min, P., Kazhdan, M., Funkhouser, T.: The Princeton shape benchmark. In: Shape Modeling International, pp. 167–388 (2004)
Sipiran, I., Bustos, B.: Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes. Vis. Comput. 27(11), 963–976 (2011)
Sun, J., Chen, X., Funkhouser, T.: Fuzzy geodesics and consistent sparse correspondences for deformable shapes. Comput. Graph. Forum 29(5), 1535–1544 (2010)
Sun, J., Ovsjanikov, M., Guibas, L.: A concise and provably informative multi-scale signature based on heat diffusion. Comput. Graph. Forum 28(5), 1383–1392 (2009)
Tabia, H., Colot, O., Daoudi, M., Vandeborre, J.P.: 3D-Shape retrieval using curves and HMM. In: IEEE International Conference on Pattern Recognition (2010)
Tierny, J., Vandeborre, J.P., Daoudi, M.: Partial 3D shape retrieval by Reeb pattern unfolding. Comput. Graph. Forum 28(1), 41–55 (2009)
Toldo, R., Castellani, U., Fusiello, A.: Visual vocabulary signature for 3D object retrieval and partial matching. In: Eurographics Workshop on 3D Object Retrieval (2009)
Vallet, B., Lévy, B.: Spectral geometry processing with manifold harmonics. Comput. Graph. Forum 27(2), 251–260 (2008)
Wang, K.: Quantization-based blind watermarking of three-dimensional meshes. Ph.d. thesis, Institut National des Sciences Appliquées de Lyon (2009)
Acknowledgements
We thank the anonymous reviewers for helping us to greatly improve this paper.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lavoué, G. Combination of bag-of-words descriptors for robust partial shape retrieval. Vis Comput 28, 931–942 (2012). https://doi.org/10.1007/s00371-012-0724-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00371-012-0724-x