Art Authentication & Painting Style Classification - PowerPoint PPT Presentation

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Art Authentication & Painting Style Classification

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  1. Art Authentication &Painting Style Classification Wan-Ting Lee Chin-Sheng Chen 4/05/2006 Multimedia Security Systems

  2. Outline • Project Objective • Introduction to Painting Style and Authors • Techniques • Schedule • Result Evaluation • References

  3. Project Objective • Art Authentication • Author Identification • Painting Styles Classification • Impressionism • Fauvism • Cubism

  4. Outline • Project Objective • Introduction to Painting Styles and Authors • Techniques • Schedule • Result Evaluation • References

  5. Introduction to Painting Style and Authors • Impressionism • Monet Claude, Pierre-Auguste Renoir, … • Fauvism • Matisse Henri, … • Cubism • Pablo Picasso, …

  6. Outline • Project Objective • Introduction to Painting Style and Authors • Techniques • Schedule • Result Evaluation • References

  7. Techniques • Author Identification • Wavelet or Pyramid Method • Find feature coefficients • Hausdorff Distance • Multidimensional Scaling • Transfer from high-dimensional vector space to low-dimensional vector space

  8. Techniques • Painting Style Classification • Four formal elements are considered: light, line, texture, and color. • Supervised Learning • Unsupervised Learning • Agglomerative Hierarchical Clustering • Self-Organizing Maps • Multidimensional Scaling

  9. Techniques

  10. Techniques

  11. Outline • Project Objective • Introduction to Painting Style and Authors • Techniques • Schedule • Result Evaluation • References

  12. Schedule

  13. Outline • Project Objective • Introduction to Painting Style and Authors • Techniques • Schedule • Result Evaluation • References

  14. Result Evaluations • Correctly and clearly define the painting belongs to whom and what kind of style • Calculate the precision region • Variance • Mean

  15. Outline • Project Objective • Introduction to Painting Style and Authors • Techniques • Schedule • Result Evaluation • References

  16. References • [1] S. Lyu, D. Rockmore and H. Farid, “A digital technique for art authentication,” PNAS, Dec. 2004 • [2] Robert W. B., and Eero P. S., “ Image compression via joint statistical characterization in the wavelet domain,” IEEE Trans. on Image Processing, Vol. 8, No. 12, Dec. 1999 • [3] Daniel P. H., Gregory A. K., and William J. R., “Comparing Images Using the Hausdorff Distance,” IEEE Trans on Pattern Analysis and Machine Intelligence, Vol. 15, No. 9, Sep. 1993 • [4] Thomas Lombardi, “The Classification of Style in Fine-Art Painting,” CSIS, Pace University, May. 2005 • [5] N.poich. The Web Museum. http://www.ibiblio.org/wm/paint/ • [6] The Museum of Modern Art. http://www.moma.org • [7] The Metropolitan Museum of Art. http://www.metmuseum.org