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High-quality tactile paintings

Published:17 November 2011Publication History
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Abstract

The aim of this work is to bring the cultural heritage of two-dimensional art closer to being accessible by blind and visually impaired people. We present a computer-assisted workflow for the creation of tactile representations of paintings, suitable to be used as a learning tool in the context of guided tours in museums or galleries. Starting from high-resolution images of original paintings, our process allows an artist to quickly design the desired form, and generate data suitable for rapid prototyping machines to produce the physical touch tools. Laser-cut layered depth diagrams convey not only the individual objects in the painting and their spatial layout, but also augment their depth relations. CNC-milled textured reliefs additionally render fine details like brush strokes and texture suitable for the sense of touch. Our methods mimic aspects of the visual sense, make sure that the haptic output is quite faithful to the original paintings, and do not require special manual abilities like sculpting skills.

References

  1. Axel, E. S. and Gerson, P. L., Eds. 2000. Art History Through Touch and Sound: A Multisensory Guide for the Blind and Visually Impaired. OpticalTouch Systems Publishers.Google ScholarGoogle Scholar
  2. Axel, E. S. and Levent, N. S., Eds. 2003. Art Beyond Sight: A Resource Guide to Art, Creativity, and Visual Impairment. AFB Press.Google ScholarGoogle Scholar
  3. Barten, P. G. J. 1999. Contrast Sensitivity of the Human Eye and its Effects on Image Quality. SPIE Press, Bellingham, WA.Google ScholarGoogle Scholar
  4. Blanz, V. and Vetter, T. 1999. A morphable model for the synthesis of 3D faces. In Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'99). ACM Press, New York, 187--194. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Borgefors, G. 1986. Distance transformations in digital images. Comput. Vis. Graph. Image Proc. 34, 344--371. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Cormen, T. H., Stein, C., Rivest, R. L., and Leiserson, C. E. 2001. Introduction to Algorithms 2nd Ed. McGraw-Hill. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Costes, E., Bassereau, J.-F., Rodi, O., and Aoussat, A. 2009. Graphic design for blind users: An industrial case study. In Proceedings of 3rd IASDR World Conference on Design Research.Google ScholarGoogle Scholar
  8. de France, F. and Icom, Eds. 1991. Museums without Barriers: A New Deal for Disabled People. Routeledge, London.Google ScholarGoogle Scholar
  9. Felzenszwalb, P. F. and Huttenlocher, D. P. 2004. Efficient graph-based image segmentation. Int. J. Comput. Vis. 59, 167--181. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Gonzalez, R. C. and Woods, R. E. 2006. Digital Image Processing 3rd Ed. Prentice Hall, Upper Saddle River, NJ. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hernandez, S. E. and Barner, K. E. 2000. Tactile imaging using watershed-based image segmentation. In Proceedings of 4th International ACM Conference on Assistive Technologies (Assets'00). ACM, New York, 26--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Hoiem, D., Efros, A. A., and Hebert, M. 2005. Automatic photo pop-up. ACM Trans. Graph. 24, 577--584. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Jayant, C., Renzelmann, M., Wen, D., Krisnandi, S., Ladner, R., and Comden, D. 2007. Automated tactile graphics translation: In the field. In Proceedings of 9th International ACM Sigaccess Conference on Computers and Accessibility (Assets'07). ACM, New York, 75--82. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Kelley, Jr, J. E. and Walker, M. R. 1959. Critical-Path planning and scheduling. In Proceedings of the IRE-AIEE-ACM'59 (Eastern) Conference. ACM, New York, 160--173. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Ladner, R. E., Ivory, M. Y., Rao, R., Burgstahler, S., Comden, D., Hahn, S., Renzelmann, M., Krisnandi, S., Ramasamy, M., Slabosky, B., Martin, A., Lacenski, A., Olsen, S., and Groce, D. 2005. Automating tactile graphics translation. In Proceedings of 7th International ACM Sigaccess Conference on Computers and Accessibility (Assets'05). ACM, 150--157. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Meyer, A., Briceño, H. M., and Bouakaz, S. 2007. User-guided shape from shading to reconstruct fine details from a single photograph. In Proceedings of the 8th Asian Conference on Computer Vision (ACCV'07). Springer-Verlag, Berlin, 738--747. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Oouchi, S., Yamazawa, K., and Secchi, L. 2010. Reproduction of tactile paintings for visual impairments utilized three-dimensional modeling system and the effect of difference in the painting size on tactile perception. In Proceedings of the 12th International Conference on Computers Helping People with Special Needs (ICCHP'10). Vol. 6180, Springer, Berlin, 527--533. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Reichinger, A., Maierhofer, S., and Purgathofer, W. 2011. High-quality tactile paintings. In EG 2011—Areas Papers, A. Day, R. Mantiuk, E. Reinhard, and R. Scopigno, Eds., Eurographics Association, 1--8.Google ScholarGoogle Scholar
  19. Russell, B. C. and Torralba, A. 2009. Building a database of 3D scenes from user annotations. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'09). IEEE, 2711--2718.Google ScholarGoogle Scholar
  20. Saxena, A., Sun, M., and Ng, A. Y. 2009. Make3D: Learning 3D scene structure from a single still image. IEEE Trans. Patt. Anal. 31, 824--840. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Shapiro, L. G. and Stockman, G. C. 2001. Computer Vision. Prentice Hall. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Smid, P. 2007. CNC Programming Handbook, 3rd Ed. Industrial Press, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Tomasi, C. and Manduchi, R. 1998. Bilateral filtering for gray and color images. In Proceedings of International Conference on Computer Vision (ICCV). IEEE Computer Society, Los Alamitos, CA, 839--846. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Ventura, J., DiVerdi, S., and Höllerer, T. 2009. A sketch-based interface for photo pop-up. In Proceedings of 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling (SBIM'09). ACM, New York, 21--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Wang, Z., Li, B., Hedgpeth, T., and Haven, T. 2009. Instant tactile-audio map: Enabling access to digital maps for people with visual impairment. In Proceedings of 11th International ACM Sigaccess Conference on Computers and Accessibility (Assets'09). ACM, New York, 43--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Wang, Z., Xu, X., and Li, B. 2008. Bayesian tactile face. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR'08). 1--8.Google ScholarGoogle Scholar
  27. Way, T. and Barner, K. 1997. Automatic visual to tactile translation. I. Human factors, access methods and image manipulation. IEEE Trans. Rehabil. Engin. 5, 1, 81--94.Google ScholarGoogle ScholarCross RefCross Ref
  28. Wu, J., Song, A., and Zou, C. 2007a. A novel haptic texture display based on image processing. In Proceedings of the IEEE International Conference on Robotics and Biometrics (ROBIO'07). 1315--1320.Google ScholarGoogle Scholar
  29. Wu, T.-P., Sun, J., Tang, C.-K., and Shum, H.-Y. 2008. Interactive normal reconstruction from a single image. ACM Trans. Graph. 27, 119:1--119:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Wu, T.-P., Tang, C.-K., Brown, M. S., and Shum, H.-Y. 2007b. ShapePalettes: Interactive normal transfer via sketching. ACM Trans. Graph. 26, 44:1--44:5. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        • Published in

          cover image Journal on Computing and Cultural Heritage
          Journal on Computing and Cultural Heritage   Volume 4, Issue 2
          November 2011
          42 pages
          ISSN:1556-4673
          EISSN:1556-4711
          DOI:10.1145/2037820
          Issue’s Table of Contents

          Copyright © 2011 ACM

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          Publication History

          • Published: 17 November 2011
          • Revised: 1 May 2011
          • Received: 1 April 2011
          Published in jocch Volume 4, Issue 2

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