Multimedia Tools and Applications

, Volume 76, Issue 3, pp 4091–4104 | Cite as

3D object retrieval based on Spatial+LDA model



Latent Dirichlet Allocation (LDA) is one popular topic extraction method, which has been applied in many applications such as textual retrieval, user recommendation system and video cluster. In this paper, we apply LDA model for visual topics extraction and utilized the topic distribution visual feature of image to handle 3D object retrieval problem. Different from the traditional LDA model, we add the spatial information of visual feature for document generation. First, we extract SIFT features from each 2D image extracted from 3D object. Then, we structure the visual documents according to the spatial information of 3D model. Finally, LDA model is used to extract the topic model for handling the retrieval problem. We further propose a multi-topic model to improve retrieval performance. Extensive comparison experiments were on the popular ETH, NTU and MV-RED 3D model datasets. The results demonstrate the superiority of the proposed method.


3D model retrieval LDA Topic model Similarity measure Topic extraction 


  1. 1.
    Ansary TF, Daoudi M, Vandeborre J-P (2007) A bayesian 3-d search engine using adaptive views clustering. IEEE Trans Multimed 9(1):78–88CrossRefGoogle Scholar
  2. 2.
    Bimbo AD, Pala P (2006) Content-based retrieval of 3d models. ACM Trans Multimed Comput Commun Appl (TOMM) 2(1):20–43CrossRefGoogle Scholar
  3. 3.
    Blei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022MATHGoogle Scholar
  4. 4.
    Bustos B, Keim DA, Saupe D, Schreck T, Vranić DV (2005) Feature-based similarity search in 3d object databases. ACM Comput Surv (CSUR) 37(4):345–387CrossRefGoogle Scholar
  5. 5.
    Chen D-Y, Tian X-P, Shen Y-T, Ouhyoung M (2003) On visual similarity based 3d model retrieval. In: Computer graphics forum, vol 22. Wiley Online Library, pp 223–232Google Scholar
  6. 6.
    Cover TM, Hart PE (1967) Nearest neighbor pattern classification. IEEE Trans Inf Theory 13(1):21–27CrossRefMATHGoogle Scholar
  7. 7.
    Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on computer vision and pattern recognition, 2005. CVPR 2005, vol 1. IEEE, pp 886–893Google Scholar
  8. 8.
    Daras P, Axenopoulos A (2010) A 3d shape retrieval framework supporting multimodal queries. Int J Comput Vis 89(2–3):229–247CrossRefGoogle Scholar
  9. 9.
    Funkhouser T, Min P, Kazhdan M, Chen J, Halderman A, Dobkin Dd, Jacobs D (2003) A search engine for 3d models. ACM Trans Graph (TOG) 22 (1):83–105CrossRefGoogle Scholar
  10. 10.
    Gao Y, Dai Q, Wang M, Zhang N (2011) 3d model retrieval using weighted bipartite graph matching. Sig Proc Image Comm 26(1):39–47CrossRefGoogle Scholar
  11. 11.
    Gao Y, Dai Q, Zhang N-Y (2010) 3d model comparison using spatial structure circular descriptor. Pattern Recogn 43(3):1142–1151CrossRefMATHGoogle Scholar
  12. 12.
    Gao Y, Tang J, Hong R, Yan S, Dai Q, Zhang N, Chua T-S (2012) Camera constraint-free view-based 3-d object retrieval. IEEE Trans Image Process 21 (4):2269–2281MathSciNetCrossRefGoogle Scholar
  13. 13.
    Guétat G, Maitre M, Joly L, Lai S-L, Lee T, Shinagawa Y (2006) Automatic 3-d grayscale volume matching and shape analysis. IEEE Trans Inf Technol Biomed 10 (2):362–376CrossRefGoogle Scholar
  14. 14.
    Hu DJ Latent dirichlet allocation for text, images, and music. University of California, San Diego. Retrieved April 26, 2013Google Scholar
  15. 15.
    Ip CY, Lapadat D, Sieger L, Regli WC (2002) Using shape distributions to compare solid models. In: Proceedings of the seventh ACM symposium on solid modeling and applications. ACM , pp 273–280Google Scholar
  16. 16.
    Kim W-Y, Kim Y-S (2000) A region-based shape descriptor using zernike moments. Signal Process Image Commun 16(1):95–102MathSciNetCrossRefGoogle Scholar
  17. 17.
    Leibe B, Schiele B (2003) Analyzing appearance and contour based methods for object categorization. In: CVPR, vol 2, pp 409–415Google Scholar
  18. 18.
    Leng B, Qin Zg, Cao X, Wei T, Zhang Z (2009) Mate: a visual based 3d shape descriptor. Chin J Electron 18(2):291–296Google Scholar
  19. 19.
    Leng B, Xiong Z (2011) Modelseek: an effective 3d model retrieval system. Multimed Tools Appl 51(3):935–962CrossRefGoogle Scholar
  20. 20.
    Li W, Bebis G, Bourbakis NG (2008) 3-d object recognition using 2-d views. IEEE Trans Image Process 17(11):2236–2255MathSciNetCrossRefGoogle Scholar
  21. 21.
    Ohbuchi R, Furuya T (2009) Scale-weighted dense bag of visual features for 3d model retrieval from a partial view 3d model. In: 2009 IEEE 12th international conference on computer vision workshops (ICCV Workshops). IEEE, pp 63–70Google Scholar
  22. 22.
    Ohbuchi R, Osada K, Furuya T, Banno T (2008) Salient local visual features for shape-based 3d model retrieval. In: IEEE international conference on shape modeling and applications, 2008. SMI 2008. IEEE, pp 93–102Google Scholar
  23. 23.
    Osada R, Funkhouser T, Chazelle B, Dobkin D (2002) Shape distributions. ACM Trans Graph (TOG) 21(4):807–832MathSciNetCrossRefMATHGoogle Scholar
  24. 24.
    Paquet E, Rioux M, Murching A, Naveen T, Tabatabai A (2000) Description of shape information for 2-d and 3-d objects. Signal Process Image Commun 16(1):103–122CrossRefGoogle Scholar
  25. 25.
    Regli WC, Cicirello VA (2000) Managing digital libraries for computer-aided design. Comput-Aided Des 32(2):119–132CrossRefGoogle Scholar
  26. 26.
    Shih J-L, Lee C-H, Wang JT (2007) A new 3d model retrieval approach based on the elevation descriptor. Pattern Recogn 40(1):283–295CrossRefMATHGoogle Scholar
  27. 27.
    Shilane P, Min P, Kazhdan M, Funkhouser T (2004) The princeton shape benchmark. In: Shape modeling applications, 2004. Proceedings. IEEE, pp 167–178Google Scholar
  28. 28.
    Sundar H, Silver D, Gagvani N, Dickinson S (2003) Skeleton based shape matching and retrieval. In: Shape modeling international, 2003. IEEE, pp 130–139Google Scholar
  29. 29.
    Tangelder JWH, Veltkamp RC (2003) Polyhedral model retrieval using weighted point sets. Int J Image Graphics 3(01):209–229CrossRefGoogle Scholar
  30. 30.
    Wang F, Li F, Dai Q, Er G (2008) View-based 3d object retrieval and recognition using tangent subspace analysis. In: Electronic Imaging 2008. International Society for Optics and Photonics, pp 68220I–68220IGoogle Scholar
  31. 31.
    Wong H-S, Ma B, Yu Z, Yeung PF, Horace HIp (2007) 3-d head model retrieval using a single face view query. IEEE Trans Multimed 9(5):1026–1036CrossRefGoogle Scholar
  32. 32.
    Yeh J-S, Chen D-Y, Chen B-Y, Ouhyoung M (2005) A web-based three-dimensional protein retrieval system by matching visual similarity. Bioinformatics 21(13):3056–3057CrossRefGoogle Scholar
  33. 33.
    Zeng J, Leng B, Xiong Z (2014) 3-d object retrieval using topic model. Multimed Tools Appl:1–23Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.School of Electronic Information EngineeringTianjin UniversityTianjinChina

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