Advertisement

Multimedia Tools and Applications

, Volume 62, Issue 3, pp 821–846 | Cite as

3D model retrieval using hybrid features and class information

  • Bo LiEmail author
  • Henry Johan
Article

Abstract

To improve the retrieval performance on a classified 3D model database, we propose a 3D model retrieval algorithm based on a hybrid 3D shape descriptor ZFDR and a class-based retrieval approach CBR utilizing the existing class information of the database. The hybrid 3D shape descriptor ZFDR comprises four features, depicting a 3D model from different aspects and it itself is already comparable to or better than several related shape descriptors. To compute the distance between a query model and a target model within a class of a database, we define an integrated distance metric which takes into account the class information. It scales the distance between the query model and the target model according to the distance between the query model and the class. Our class-based retrieval approach CBR is general, it can be used with any shape descriptors to improve their retrieval performance. Extensive generic and partial 3D model retrieval experiments on seven standard databases demonstrate that after we employ CBR, the retrieval performance of our algorithm CBR-ZFDR is evidently improved and the result is better than that achieved by the state-of-the-art method on each database in terms of most of the commonly used performance metrics.

Keywords

3D model retrieval Hybrid shape descriptor Class information Integrated distance 

References

  1. 1.
    AIM@SHAPE (2010) SHREC contest. Home page http://www.aimatshape.net/event/SHREC/. Accessed 2011
  2. 2.
    Ankerst M, Kastenmüller G, Kriegel HP, Seidl T (1999) 3D shape histograms for similarity search and classification in spatial databases. In: Güting RH, Papadias D, Lochovsky FH (eds) SSD. Lecture notes in computer science, vol 1651. Springer, New York, pp 207–226Google Scholar
  3. 3.
    Axenopoulos A, Litos G, Daras P (2011) 3D model retrieval using accurate pose estimation and view-based similarity. In: De Natale FGB, Del Bimbo A, Hanjalic A, Manjunath BS, Satoh S (eds) Proceedings of the 1st international conference on multimedia retrieval, ICMR 2011. Trento, Italy, 18–20 April 2011Google Scholar
  4. 4.
    Ben-Chen M, Gotsman C (2008) Characterizing shape using conformal factors. In: Eurographics workshop on 3D object retrieval, 3DOR 2008, pp 1–8Google Scholar
  5. 5.
    Biasotti S, Marini S (2006) Sub-part correspondence using structure and geometry. In: Gallo G, Battiato S, Stanco F (eds) Eurographics Italian chapter conference, Eurographics, pp 23–28Google Scholar
  6. 6.
    Biasotti, S, Giorgi D, Marini S, Spagnuolo M, Falcidieno B (2007) 3D classification via structural prototypes. In: Falcidieno B, Spagnuolo M, Avrithis YS, Kompatsiaris I, Buitelaar P (eds) SAMT, Lecture notes in computer science, vol 4816. Springer, New York, pp 140–143Google Scholar
  7. 7.
    Bustos B, Keim DA, Saupe D, Schreck T, Vranic DV (2004) Using entropy impurity for improved 3D object similarity search. In: ICME. IEEE, Piscataway, pp 1303–1306Google Scholar
  8. 8.
    Chaouch M, Verroust-Blondet A (2007) A new descriptor for 2D depth image indexing and 3D model retrieval. In: ICIP (6). IEEE, Piscataway, pp 373–376Google Scholar
  9. 9.
    Chen DY, Tian XP, Shen YT, Ouhyoung M (2003) On visual similarity based 3D model retrieval. Comput Graph Forum 22(3):223–232CrossRefGoogle Scholar
  10. 10.
    Cohen SD, Guibas LJ (1999) The Earth mover’s distance under transformation sets. In: ICCV, pp 1076–1083Google Scholar
  11. 11.
    Cornea ND, Demirci MF, Silver D, Shokoufandeh A, Dickinson SJ, Kantor PB (2005) 3D object retrieval using many-to-many matching of curve skeletons. In: SMI. IEEE Computer Society, Los Alamitos, pp 368–373Google Scholar
  12. 12.
    Fang R, Godil A, Li X, Wagan A (2008) A new shape benchmark for 3D object retrieval. In: Bebis G et al (eds) ISVC (1). Lecture notes in computer science, vol 5358. Springer, New York, pp 381–392Google Scholar
  13. 13.
    Funkhouser T, Min P, Kazhdan M, Chen J, Halderman A, Dobkin D, Jacobs D (2003) A search engine for 3D models. ACM Trans Graph 22(1):83–105CrossRefGoogle Scholar
  14. 14.
    Godil A et al (2009) SHREC ’09 track: generic shape retrieval. In: Eurographics workshop on 3D object retrieval, 3DOR 2009, pp 61–68Google Scholar
  15. 15.
    Han EH, Karypis G (2000) Centroid-based document classification: analysis and experimental results. In: Zighed DA et al (eds) PKDD, Lecture notes in computer science, vol 1910, Springer, New York, pp 424–431Google Scholar
  16. 16.
    Hilaga M, Shinagawa Y, Komura T, Kunii TL (2001) Topology matching for fully automatic similarity estimation of 3D shapes. In: SIGGRAPH 2001, pp 203–212Google Scholar
  17. 17.
    Horn B (1984) Extended Gaussian images. Proc IEEE 72(12):1671–1686CrossRefGoogle Scholar
  18. 18.
    Hou S, Lou K, Ramani K (2005) SVM-based semantic clustering and retrieval of a 3D model database. CAD Appl 2:155–164Google Scholar
  19. 19.
    Iyer N, Jayanti S, Lou K, Kalyanaraman Y, Ramani K (2005) Three-dimensional shape searching: state-of-the-art review and future trends. CAD 37(5):509–530Google Scholar
  20. 20.
    Järvelin K, Kekäläinen J (2002) Cumulated gain-based evaluation of ir techniques. ACM Trans Inf Sys 20(4):422–446CrossRefGoogle Scholar
  21. 21.
    Jayanti S, Kalyanaraman Y, Iyer N, Ramani K (2006) Developing an engineering shape benchmark for CAD models. CAD 38(9):939–953Google Scholar
  22. 22.
    Kazhdan MM, Funkhouser TA, Rusinkiewicz S (2003) Rotation invariant spherical harmonic representation of 3D shape descriptors. In: Symposium on geometry processing, pp 156–164Google Scholar
  23. 23.
    Khotanzad A, Hong Y (1990) Invariant image recognition by Zernike moments. IEEE Trans Pattern Anal Mach Intell 12(5):489–497CrossRefGoogle Scholar
  24. 24.
    Laga H, Nakajima, M (2008) Supervised learning of similarity measures for content-based 3D model retrieval. In: Tokunaga T, Ortega A (eds) LKR. Lecture notes in computer science, vol 4938. Springer, New York, pp 210–225Google Scholar
  25. 25.
    Leng B, Xiong Z (2011) Modelseek: an effective 3D model retrieval system. Multimedia Tools Appl 51:935–962CrossRefGoogle Scholar
  26. 26.
    Lian Z, Godil A, Sun X (2010) Visual similarity based 3D shape retrieval using bag-of-features. In: Shape modeling international. IEEE Computer Society, Los Alamitos, pp 25–36Google Scholar
  27. 27.
    Lian Z, Rosin P, Sun X (2010) Rectilinearity of 3D meshes. Int J Comput Vis 89(2):130–151CrossRefGoogle Scholar
  28. 28.
    Liu X, Croft WB (2004) Cluster-based retrieval using language models. In: 27th annual international ACM SIGIR conference (SIGIR 2004), pp 186–193Google Scholar
  29. 29.
    Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110CrossRefGoogle Scholar
  30. 30.
    Ohbuchi R, Osada K, Furuya T, Banno T (2008) Salient local visual features for shape-based 3D model retrieval. In: Shape modeling international. IEEE, Piscataway, pp 93–102Google Scholar
  31. 31.
    Osada R, Funkhouser TA, Chazelle B, Dobkin DP (2001) Matching 3D models with shape distri butions. In: Shape modeling international. IEEE Computer Society, Los Alamitos, pp 154–166Google Scholar
  32. 32.
    Papadakis P, Pratikakis I, Theoharis T, Passalis G, Perantonis SJ (2008) 3D object retrieval using an efficient and compact hybrid shape descriptor. In: Eurographics workshop on 3D object retrieval, 3DOR 2008, pp 9–16Google Scholar
  33. 33.
    Papadakis P, Pratikakis I, Theoharis T, Perantonis S (2010) PANORAMA: a 3D shape descriptor based on panoramic views for unsupervised 3D object retrieval. Int J Comput Vis 89(2–3):177–192. http://www.dis.uniroma1.it/~papadakis/ CrossRefGoogle Scholar
  34. 34.
    Shih JL, Chen HY (2009) A 3D model retrieval approach using the interior and exterior 3D shape information. Multimedia Tools Appl 43(1):45–62CrossRefGoogle Scholar
  35. 35.
    Shilane P, Min P, Kazhdan MM, Funkhouser TA (2004) The Princeton shape benchmark. In: Shape Modeling International. IEEE Computer Society, Los Alamitos, pp 167–178Google Scholar
  36. 36.
    Siddiqi K, Zhang J, Macrini D, Shokoufandeh A, Bouix S, Dickinson SJ (2008) Retrieving articulated 3-D models using medial surfaces. Mach Vis Appl 19(4):261–275CrossRefGoogle Scholar
  37. 37.
    Sundar H, Silver D, Gagvani N, Dickinson SJ (2003) Skeleton based shape matching and retrieval. In: Shape modeling international. IEEE Computer Society, Los Alamitos, pp 130–139CrossRefGoogle Scholar
  38. 38.
    Tangelder JWH, Veltkamp RC (2008) A survey of content based 3D shape retrieval methods. Multimedia Tools Appl 39(3):441–471CrossRefGoogle Scholar
  39. 39.
    Tatsuma A, Aono M (2009) Multi-fourier spectra descriptor and augmentation with spectral clustering for 3D shape retrieval. Vis Comput 25(8):785–804CrossRefGoogle Scholar
  40. 40.
    Tierny J, Vandeborre JP, Daoudi M (2009) Partial 3D shape retrieval by reeb pattern unfolding. Comput Graph Forum 28(1):41–55CrossRefGoogle Scholar
  41. 41.
    Toldo R, Castellani U, Fusiello A (2009) Visual vocabulary signature for 3D object retrieval and partial matching. In: Eurographics workshop on 3D object retrieval, 3DOR 2009, pp 21–28Google Scholar
  42. 42.
    Veltkamp RC, ter Haar FB (2007) SHREC 2007 3D retrieval contest. Technical report UU-CS-2007-015, Department of Information and Computing Sciences, Utrecht UniversityGoogle Scholar
  43. 43.
    Vranic D (2004) 3D model retrieval. PhD thesis, University of LeipzigGoogle Scholar
  44. 44.
    Vranic DV (2005) DESIRE: a composite 3D-shape descriptor. In: ICME. IEEE, Piscataway, pp 962–965Google Scholar
  45. 45.
    Wessel R, Blümel I, Klein R (2009) A 3D shape benchmark for retrieval and automatic classification of architectural data. In: Eurographics workshop on 3D object retrieval, 3DOR 2009, pp 53–56Google Scholar
  46. 46.
    Xu D, Li H (2007) 3D shape retrieval integrated with classification information. In: Fourth international conference on image and graphics, 2007. ICIG 2007, pp 774 –779Google Scholar
  47. 47.
    Zhang D, Luo G (2001) A comparative study on shape retrieval using Fourier descriptors with different shape signatures. In: Proc. of international conference on intelligent multimedia and distance education (ICIMADE01), pp 1–9Google Scholar
  48. 48.
    Zhang D, Luo G (2002) An integrated approach to shape based image retrieval. In: Proc. of the 5th Asian conference on computer vision (ACCV 2002), pp 652–657Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.School of Computer EngineeringNanyang Technological UniversitySingaporeSingapore

Personalised recommendations