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A new sketch-based 3D model retrieval method by using composite features

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Abstract

With the rapid growth of available 3D models in various areas, effective methods to search 3D models are becoming increasingly important. In this paper, we propose a new method for sketch-based 3D model retrieval. Different from current methods that make use of either global or local features, the proposed method uses composite features combining global and local features extracted from representative 2D views of 3D models. The global features, shape strings, represent exterior boundary shape of the views and the local features, improved Pyramid of Histograms of Orientation Gradients (iPHOG), represent their interior details. Specifically, a global feature based filtering step is adopted to select more relevant candidate models to the query sketch and a local feature based process is used to refine chosen candidates. To evaluate the performance of the proposed method with that of other previous ones, we conducted a series of experiments on public standard 3D model databases. Experimental results are presented and indicate the effectiveness of the new approach for sketch-based 3D model retrieval.

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References

  1. Amayeh G, Erol A, Bebis G, Nicolescu M (2005) Accurate and efficient computation of high order zernike moments Advances in visual computing, pp 462–469. Springer

  2. Ankerst M, Kastenmüller G, Kriegel HP, Seidl T (1999) 3d shape histograms for similarity search and classification in spatial databases Advances in Spatial Databases, pp 207–226. Springer

  3. Barra V, Biasotti S (2014) 3d shape retrieval and classification using multiple kernel learning on extended reeb graphs. Vis Comput 30(11):1247–1259

    Article  Google Scholar 

  4. Belongie S, Malik J, Puzicha J (2002) Shape matching and object recognition using shape contexts. IEEE Trans Pattern Anal Mach Intell 24(4):509–522

    Article  Google Scholar 

  5. Bosch A, Zisserman A, Munoz X (2007) Representing shape with a spatial pyramid kernel Proceedings of the 6th ACM international conference on Image and video retrieval, pp 401–408. ACM

  6. Canny J (1986) A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell 8:679–698

    Article  Google Scholar 

  7. Chen DY, Tian XP, Shen YT, Ouhyoung M (2003) On visual similarity based 3d model retrieval Computer graphics forum, vol. 22, pp 223–232. Wiley Online Library

  8. Cole F, Sanik K, DeCarlo D, Finkelstein A, Funkhouser T, Rusinkiewicz S, Singh M (2009) How well do line drawings depict shape? ACM Transactions on Graphics (TOG), vol. 28, p 28. ACM

  9. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp 886–893. IEEE

  10. Daras P, Axenopoulos A (2010) A 3d shape retrieval framework supporting multimodal queries. Int J Comput Vis 89(2-3):229–247

    Article  Google Scholar 

  11. DeCarlo D, Finkelstein A, Rusinkiewicz S, Santella A (2003) Suggestive contours for conveying shape ACM Transactions on Graphics (TOG), vol. 22, pp 848–855. ACM

  12. Eitz M, Richter R, Boubekeur T, Hildebrand K, Alexa M (2012) Sketch-based shape retrieval. ACM Trans Graph 31(4):31

    Google Scholar 

  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):83–105

    Article  Google Scholar 

  14. Furuya T, Ohbuchi R (2013) Ranking on cross-domain manifold for sketch-based 3d model retrieval Cyberworlds (CW), 2013 International Conference on, pp 274–281. IEEE

  15. Furuya T, Ohbuchi R (2015) Similarity metric learning for sketch-based 3d object retrieval. Mult Tools Appl 74(23):10,367–10,392

    Article  Google Scholar 

  16. Körtgen M., Park GJ, Novotni M, Klein R (2003) 3d shape matching with 3d shape contexts The 7th central European seminar on computer graphics, vol. 3, pp 5–17

  17. Lavoué G (2012) Combination of bag-of-words descriptors for robust partial shape retrieval. Vis Comput 28(9):931–942

    Article  Google Scholar 

  18. Lazebnik S, Schmid C, Ponce J (2006) Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp 2169–2178. IEEE

  19. Li B, Johan H (2013) Sketch-based 3d model retrieval by incorporating 2d-3d alignment. Mult Tools Appl 65(3):363–385

    Article  Google Scholar 

  20. Li B, Lu Y, Godil A, Schreck T, Aono M, Johan H, Saavedra JM, Tashiro S (2013) Shrec’13 track: large scale sketch-based 3d shape retrieval Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval, pp 89–96. Eurographics Association

  21. Li B, Lu Y, Godil A, Schreck T, Bustos B, Ferreira A, Furuya T, Fonseca MJ, Johan H, Matsuda T, et al (2014) A comparison of methods for sketch-based 3d shape retrieval. Comput Vis Image Underst 119:57–80

    Article  Google Scholar 

  22. Li B, Lu Y, Johan H (2013) Sketch-based 3d model retrieval by viewpoint entropy-based adaptive view clustering Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval, pp 49–56. Eurographics Association

  23. Li B, Lu Y, Li C, Godil A, Schreck T, Aono M, Burtscher M, Fu H, Furuya T, Johan H, et al (2014) Shrec’14 track: extended large scale sketch-based 3d shape retrieval Eurographics Workshop on 3D Object Retrieval, pp 121–130

  24. Liu YJ, Luo X, Joneja A, Ma CX, Fu XL, Song D (2013) User-adaptive sketch-based 3d cad model retrieval. IEEE Trans Autom Sci Eng 10:783–795

    Article  Google Scholar 

  25. Loffler J (2000) Content-based retrieval of 3d models in distributed web databases by visual shape information IEEE International Conference on Information Visualization, pp 82–87. IEEE

  26. Nie W, Li X, Liu A, Su Y (2015) 3d object retrieval based on spatial+ lda model. Multimedia Tools and Applications pp 1–14

  27. Osada R, Funkhouser T, Chazelle B, Dobkin D (2002) Shape distributions. ACM Trans Graph 21(4):807–832

    Article  MathSciNet  MATH  Google Scholar 

  28. Petrou M, Petrou C (2010) Image processing: the fundamentals. Wiley

  29. Podolak J, Shilane P, Golovinskiy A, Rusinkiewicz S, Funkhouser T (2006) A planar-reflective symmetry transform for 3d shapes ACM Transactions on Graphics (TOG), vol. 25, pp 549–559. ACM

  30. Saavedra JM, Bustos B (2010) An improved histogram of edge local orientations for sketch-based image retrieval Pattern Recognition, pp 432–441. Springer

  31. Saavedra JM, Bustos B, Scherer M, Schreck T (2011) Stela: sketch-based 3d model retrieval using a structure-based local approach Proceedings of the 1st ACM International Conference on Multimedia Retrieval, p 26. ACM

  32. Secord A, Lu J, Finkelstein A, Singh M, Nealen A (2011) Perceptual models of viewpoint preference. ACM Trans Graph 30(5):109

    Article  Google Scholar 

  33. Shao T, Xu W, Yin K, Wang J, Zhou K, Guo B (2011) Discriminative sketch-based 3d model retrieval via robust shape matching Computer Graphics Forum, vol. 30. Wiley Online Library

  34. Shih JL, Chen HY (2009) A 3d model retrieval approach using the interior and exterior 3d shape information. Mult Tools Appl 43(1):45–62

    Article  Google Scholar 

  35. Shilane P, Min P, Kazhdan M, Funkhouser T (2004) The princeton shape benchmark Proceedings of Shape Modeling Applications, pp 167–178. IEEE

  36. Sivic J, Zisserman A (2003) Video google: A text retrieval approach to object matching in videos Ninth IEEE International Conference on Computer Vision, pp 1470–1477. IEEE

  37. Tangelder JW, Veltkamp RC (2008) A survey of content based 3d shape retrieval methods. Mult Tools Appl 39(3):441–471

    Article  Google Scholar 

  38. Veltkamp RC, Hagedoorn M (2001) Principles of Visual Information Retrieval, chap. State of the Art in Shape Matching, pp 87–119. Springer, London

    Google Scholar 

  39. Vranic DV, Saupe D, Richter J (2001) Tools for 3d-object retrieval: Karhunen-loeve transform and spherical harmonics IEEE Fourth Workshop on Multimedia Signal Processing, pp 293–298. IEEE

  40. Yoon SM, Scherer M, Schreck T, Kuijper A (2010) Sketch-based 3d model retrieval using diffusion tensor fields of suggestive contours Proceedings of the international conference on Multimedia, pp 193–200. ACM

  41. Zhao L, Liang S, Jia J, Wei Y (2015) Learning best views of 3d shapes from sketch contour. The Visual Computer pp 1–10

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Acknowledgments

This research is jointly supported by the National Natural Science Foundation of China (U1504608, 61602222, 61572531), and the Jiangxi Natural Science Foundation (No.20161BAB212043).

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Authors and Affiliations

  1. Software Engineering College, Zhengzhou University of Light Industry, Zhengzhou, 450001, China

    Yuhua Li

  2. School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, 330022, China

    Haopeng Lei

  3. School of Communication and Design, Sun Yat-sen University, Guangzhou, 510006, China

    Shujin Lin

  4. School of Software, Jiangxi Normal University, Nanchang, 330022, China

    Guoliang Luo

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  1. Yuhua Li
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  2. Haopeng Lei
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  3. Shujin Lin
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  4. Guoliang Luo
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Correspondence to Haopeng Lei.

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Li, Y., Lei, H., Lin, S. et al. A new sketch-based 3D model retrieval method by using composite features. Multimed Tools Appl 77, 2921–2944 (2018). https://doi.org/10.1007/s11042-017-4446-y

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  • DOI: https://doi.org/10.1007/s11042-017-4446-y

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