Predictive digitisation of cultural heritage objects

  • Ioannis Pratikakis
  • Michalis A. Savelonas
  • Pavlos Mavridis
  • Georgios Papaioannou
  • Konstantinos Sfikas
  • Fotis Arnaoutoglou
  • Dirk Rieke-Zapp
Article

Abstract

3D digitisation has been instrumental in the cultural heritage domain for over a decade, contributing to the digital preservation and dissemination of cultural heritage. Still, the typical 3D acquisition workflow remains complex and time-consuming. This work presents the concept of predictive digitisation by means of a platform, aiming to speed-up and simplify 3D digitisation, exploiting similarities in digital repositories of Cultural Heritage objects.

Keywords

3D object retrieval Rigid registration Non-rigid registration Cultural heritage 

Notes

Acknowledgements

This work was supported by the EC FP7 STREP Project PRESIOUS, grant no. 600533.

References

  1. 1.
    Arandjelović R, Zisserman A (2012) Three things everyone should know to improve object retrieval. In: Proc CVPR, pp 2911–2918Google Scholar
  2. 2.
    Bhattacharyya A (1943) On a measure of divergence between two statistical populations defined by their probability distributions. Bull Calcutta Math Soc 35:99–109MathSciNetMATHGoogle Scholar
  3. 3.
    Bosch A, Zisserman A (2007) Image classification using random forests and ferns. In: Proc ICCV, pp 1–8Google Scholar
  4. 4.
    Bouaziz S, Tagliasacchi A, Pauly M (2013) Sparse iterative closest point. Comput Graph Forum (Symp Geom Process) 32(5):1–11CrossRefGoogle Scholar
  5. 5.
    Chatfield K, Lempitsky VS, Vedaldi A, Zisserman A (2011) The devil is in the details: an evaluation of recent feature encoding methods. In: Proc BMVC, pp 1–12Google Scholar
  6. 6.
    Furuya T, Ohbuchi R (2009) Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features. In: Proc. ACM int. conf. image and video retrievalGoogle Scholar
  7. 7.
    Gao L, Song J, Liu X, Shao J, Liu J, Shao J (2015) Learning in high-dimensional multimedia data: the state of the art. Multimed Syst 1–11Google Scholar
  8. 8.
    Jegou H, Perronnin F, Douze M, Sánchez J, Perez P, Schmid C (2012) Aggregating local image descriptors into compact codes. IEEE Trans Pattern Anal Mach Intell 34(9):1704–1716CrossRefGoogle Scholar
  9. 9.
    Kazhdan M, Bolitho M, Hoppe H (2006) Poisson surface reconstruction. In: Proc SGP, pp 61–70Google Scholar
  10. 10.
    Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110CrossRefGoogle Scholar
  11. 11.
    Lu G, Yan Y, Ren L, Song J, Sebe N, Kambhamettu C (2015) Localize me anywhere, anytime: a multi-task point-retrieval approach. Proc ICCV 60 (2):2434–2442Google Scholar
  12. 12.
    Mavridis P, Andreadis A, Papaioannou G (2015) Efficient sparse {ICP}. Comput Aided Geome Des 35–36:16–26MathSciNetCrossRefGoogle Scholar
  13. 13.
    Mavridis P, Sipiran I, Andreadis A, Papaioannou G (2015) Object completion using k-sparse optimization. Comput Graph Forum 34(7):13–21CrossRefGoogle Scholar
  14. 14.
    Museth K (2013) VDB: High-resolution sparse volumes with dynamic topology. ACM Trans Graph 32:3CrossRefMATHGoogle Scholar
  15. 15.
    Papazov C, Burschka D (2011) Deformable 3D shape registration based on local similarity transforms. Comput Graph Forum 30(5):1493–1502CrossRefGoogle Scholar
  16. 16.
    Pauly M, Mitra NJ, Giesen J, Gross M, Guibas LJ (2005) Example-based 3D scan completion. In: Proc SGP, no. 23Google Scholar
  17. 17.
    Perronnin F, Dance CR (2007) Fisher kernels on visual vocabularies for image categorization. In: Proc. CVPRGoogle Scholar
  18. 18.
    Pratikakis I, Savelonas MA, Arnaoutoglou F, Ioannakis G, Koutsoudis A, Theoharis T, Tran M-T, Nguyen V-T, Pham V-K, Nguyen H-D, Le H-A, Tran B-H, To H-Q, Truong M-B, Phan TV, Nguyen M -D, Than T-A, Mac C-K-N, Do MN, Duong A-D, Furuya T, Ohbuchi R, Aono M, Tashiro S, Pickup D, Sun X, Rosin PL, Martin RR (2016) SHREC 2016 track on partial shape queries for 3D object retrieval. In: Proc 3DOR, pp 79–88Google Scholar
  19. 19.
    Sánchez J, Perronnin F, Mensink T, Verbeek JJ (2013) Image classification with the Fisher vector: theory and practice. Int J Comput Vis 105(3):222–245MathSciNetCrossRefMATHGoogle Scholar
  20. 20.
    Savelonas M, Pratikakis I, Sfikas K (2015) Overview of partial 3D object retrieval methodologies. Multimed Tools Appl 74(24):11783–11808CrossRefGoogle Scholar
  21. 21.
    Sfikas K, Pratikakis I, Koutsoudis A, Savelonas M, Theoharis T (2016) Partial matching of 3D cultural heritage objects using panoramic views. Multimed Tools Appl 75(7):3693–3707CrossRefGoogle Scholar
  22. 22.
    Shilane P, Min P, Kazhdan MM, Funkhouser TA (2004) The Princeton shape benchmark. In: Proc SMI, pp 167–178Google Scholar
  23. 23.
    Siarry P, Berthiau G, Durdin F, Haussy J (1997) Enhanced simulated annealing for globally minimizing functions of many-continuous variables. ACM Trans Math Softw 23(2):209–228MathSciNetCrossRefMATHGoogle Scholar
  24. 24.
    Song J, Yang Y, Li X, Huang Z, Yang Y (2014) Robust hashing with local models for approximate similarity search. IEEE Trans Cybern 44(7):1225–1236CrossRefGoogle Scholar
  25. 25.
    Tao R, Gavves E, Snoek CGM, Smeulders AWM (2014) Locality in generic instance search from one example. In: Proc CVPR, pp 2099–2106Google Scholar
  26. 26.
    Wang J, Wang J, Song J, Xu X-S, Shen HT, Li S (2014) Optimized Cartesian k-means. IEEE Trans Knowl Data Eng 27:180–192CrossRefGoogle Scholar
  27. 27.
    Wang J, Zhang T, Song J, Sebe N, Shen HT (2016) A survey on learning to hash. arXiv:1606.00185
  28. 28.
    Zhou X, Yu K, Zhang T, Huang TS (2010) Image classification using super-vector coding of local image descriptors. In: Proc. ECCVGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Democritus University of ThraceXanthiGreece
  2. 2.ATHENA Research and Innovation CenterXanthiGreece
  3. 3.Graz University of TechnologyGrazAustria
  4. 4.Athens University of Economics and BusinessAthensGreece
  5. 5.NTNUTrondheimNorway
  6. 6.AICON 3D systems, GmbHBraunschweigGermany

Personalised recommendations