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Shape-based indexing scheme for camera view invariant 3-D object retrieval

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Abstract

Camera view invariant 3-D object retrieval is an important issue in many traditional and emerging applications such as security, surveillance, computer-aided design (CAD), virtual reality, and place recognition. One straightforward method for camera view invariant 3-D object retrieval is to consider all the possible camera views of 3-D objects. However, capturing and maintaining such views require an enormous amount of time and labor. In addition, all camera views should be indexed for reasonable retrieval performance, which requires extra storage space and maintenance overhead. In the case of shape-based 3-D object retrieval, such overhead could be relieved by considering the symmetric shape feature of most objects. In this paper, we propose a new shape-based indexing and matching scheme of real or rendered 3-D objects for camera view invariant object retrieval. In particular, in order to remove redundant camera views to be indexed, we propose a camera view skimming scheme, which includes: i) mirror shape pairing and ii) camera view pruning according to the symmetrical patterns of object shapes. Since our camera view skimming scheme considerably reduces the number of camera views to be indexed, it could relieve the storage requirement and improve the matching speed without sacrificing retrieval accuracy. Through various experiments, we show that our proposed scheme can achieve excellent performance.

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References

  1. Ankerst M, Kastenmuller G, Kriegel H-P, Seidl T (1999) 3D shape histograms for similarity search and classification in spatial databases. International Symposium on Advances in Spatial Databases 207–226

  2. Aouat S, Laichea N, Souamia F, Larabi S (2007) 3D object indexing and recognition. Appl Math Comput 196(1):318–332

    Article  Google Scholar 

  3. Bustos B, Keim DA, Saupe D, Schreck T, Vranic DV (2005) Feature-based similarity search in 3D object databases. ACM Comput Surv 37(4):345–387

    Article  Google Scholar 

  4. Chen D-Y, Tian X-P, Shen Y-T, Ouhyoung M (2003) On visual similarity based 3D model retrieval. Comput Graph Forum 22(3):223–232

    Article  Google Scholar 

  5. Ding H, Trajcevski G, Scheuermann P (2008) Efficient similarity join of large sets of moving object trajectories. International Symposium on Temporal Representation and Reasoning 79–87

  6. Faloutsos C., Lin K (1995) FastMap: A fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets. ACM SIGMOD 163–174

  7. Faloutsos C, Ranganathan M, Manolopoulos Y (1993) Fast subsequence matching in time-series databases. ACM SIGMOD 419–429

  8. Faloutsos C, Barber R, Flickner M, Hafner J, Niblack W, Petkovic D, Equitz W (1994) Efficient and effective querying by image content. Journal of Intelligent Information Systems Archive 3(3–4):231–262

    Article  Google Scholar 

  9. Guttman A (1984) R-trees: a dynamic index structure for spatial searching. ACM SIGMOD 47–57

  10. Han W, Lee J, Moon Y, Jiang H (2007) Fast ranked subsequence matching in time-series databases. International Conference on Very Large Data Bases 423–434

  11. Heczko M, Keim DA, Saupe D, Vranic D (2002) Methods for similarity search on 3D databases. Datenbank-Spektrum 54–63

  12. Horn B (1984) Extended Gaussian images. Proc IEEE 1671–1686

  13. Ip H, Wong W (2002) 3D head models retrieval based on hierarchical facial region similarity. International Conference on Vision Interface 314–319

  14. Kato T, Suzuki M, Otsu N (2000) A similarity retrieval of 3D polygonal models using rotation invariant shape descriptors. International Conference on Systems, Man, and Cybernetics 2946–2952

  15. Keogh E, Chakrabarti K, Pazzani M, Mehrotra S (2001) Locally adaptive dimensionality reduction for indexing large time series databases. ACM SIGMOD 151–162

  16. Keogh E, Ratanamahatana C (2004) Exact indexing of dynamic time warping. Knowl Inf Syst 7:358–386

    Article  Google Scholar 

  17. Keogh E, Wei L, Xi X, Lee S, Vlachos M (2006) LB_Keogh supports exact indexing of shapes under rotation invariance with arbitrary representations and distance measures. International Conference on Very Large Data Bases 882–893.

  18. Kim S, Park S, Chu W (2001) An index-based approach for similarity search supporting time warping in large sequence databases. International Conference on Data Engineering 607–614

  19. Nguyen P, Shiri N (2008) Fast correlation analysis on time series datasets. ACM conference on Information and knowledge management 787–796

  20. Papadakis P, Pratikakis I, Theoharis T, Passalis G, Perantonis S (2008) 3D Object Retrieval using an Efficient and Compact Hybrid Shape Descriptor. Eurographics Workshop on 3D Object Retrieval 9–16

  21. Shum H-Y, Hebert M, Ikeuchi K (1996) On 3D shape similarity. International Conference on Computer Vision and Pattern Recognition 526–531

  22. Struzik ZR, Siebes A (1999) The Haar wavelet transform in the time series similarity paradigm. Lect Notes Comput Sci 1704:12–22

    Google Scholar 

  23. Tak Y., Hwang E (2007). A leaf image retrieval scheme based on partial dynamic time warping and two-level filtering. International Conference on Computer and Information Technology 663–638. Oct

  24. Tak Y, Hwang E (2008) An indexing scheme for efficient camera angle invariant image retrieval. International Conference on Computer and Information Technology, 143–148.

  25. Tangelder JWH, Veltkamp RC (2008) A survey of content based 3D shape retrieval methods. Multimed Tools Appl 39(3)

  26. Vranic D (2004) 3D model retrieval. Ph.D. Thesis, University of Leipzig, Germany

  27. Vranic D, Saupe D (2001) 3D shape descriptor based on 3D Fourier transform. EURASIP Conference on Digital Signal Processing for Multimedia Communications and Services 271–274

  28. Wang Z, Chi Z, Feng D, Wang Q (2000) Leaf image retrieval with shape features. Lect Note Comput Sci 1929:477–487

    Article  Google Scholar 

  29. Yi B, Jagadish H, Faloutsos C (1998) Efficient retrieval of similar time sequences under time warping. International Conference on Data Engineering 23–27

  30. Zaharia T, Preteux F (2001) Three dimensional shape-based retrieval within the MPEG-7 framework. In Proceedings of the SPIE Conference on Nonlinear Image Processing and Pattern Analysis XII, 133–145

  31. Zhu Y, Shasha D (2003) Warping indexes with envelope transforms for query by humming. ACM SIGMOD 181–192

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Acknowledgement

This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD) (KRF-2008-313-D00858).

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Authors and Affiliations

  1. Graduate School of Information Management & Security, Korea University, Anam-Dong, Seongbuk-Gu, Seoul, Republic of Korea

    Hyoung Joong Kim

  2. School of Electrical Engineering, Korea University, Anam-Dong, Seongbuk-Gu, Seoul, Republic of Korea

    Yoon-Sik Tak & Eenjun Hwang

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  1. Hyoung Joong Kim
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  2. Yoon-Sik Tak
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Correspondence to Eenjun Hwang.

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Kim, H.J., Tak, YS. & Hwang, E. Shape-based indexing scheme for camera view invariant 3-D object retrieval. Multimed Tools Appl 47, 7–29 (2010). https://doi.org/10.1007/s11042-009-0404-7

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