Identifying painters from color profiles of skin patches in painting images

Research on digital analysis of painting images has received very little attention. The exact nature of scientific methods seems to be antithesis of art. Nevertheless, several papers have proposed methods to bridge this gap and have obtained interesting results. In fact, some art theorists have pointed out the usefulness of specific quantifiable features in the paintings. This paper presents a method for identifying painters using color profiles of skin patches in painting images. Various color models for representing the color profiles were explored. Various implementations of multiclass support vector machine classfiiers were compared. We found that a weighted combination of several directed acyclic graph SVMs with Gaussian kernels gives the best classification performance.

[1]  Thomas Ertl,et al.  Computer Graphics - Principles and Practice, 3rd Edition , 2014 .

[2]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[3]  Bruce Cole,et al.  The Renaissance Artist at Work: From Pisano to Titian , 1983 .

[4]  Gérard Dreyfus,et al.  Single-layer learning revisited: a stepwise procedure for building and training a neural network , 1989, NATO Neurocomputing.

[5]  J. Meigs,et al.  WHO Technical Report , 1954, The Yale Journal of Biology and Medicine.

[6]  Kristin P. Bennett,et al.  Multicategory Classification by Support Vector Machines , 1999, Comput. Optim. Appl..

[7]  Kozaburo Hachimura.  Retrieval of paintings using principal color information , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[8]  Sayan Mukherjee,et al.  Feature Selection for SVMs , 2000, NIPS.

[9]  Matthew Anderson,et al.  Proposal for a Standard Default Color Space for the Internet - sRGB , 1996, CIC.

[10]  Henri Maitre,et al.  High-quality imaging in museum: from theory to practice , 1997, Electronic Imaging.

[11]  Jason Weston,et al.  Multi-Class Support Vector Machines , 1998 .

[12]  M. Carter.  Computer graphics: Principles and practice , 1997 .

[13]  B. Barsky,et al.  An Introduction to Splines for Use in Computer Graphics and Geometric Modeling , 1987 .

[14]  Koby Crammer,et al.  On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines , 2002, J. Mach. Learn. Res..

[15]  R. Berns.  Billmeyer and Saltzman's Principles of Color Technology , 2000 .

[16]  Thomas G. Dietterich,et al.  Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs , 1991, AAAI.

[17]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Eric O. Postma,et al.  Discovering the Visual Signature of Painters , 2000 .

[19]  Nello Cristianini,et al.  An introduction to Support Vector Machines , 2000 .

[20]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[21]  M. F.,et al.  Bibliography , 1985, Experimental Gerontology.

[22]  Yoram Singer,et al.  Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers , 2000, J. Mach. Learn. Res..

[23]  Alberto Del Bimbo,et al.  A visual language for color-based painting retrieval , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[24]  Sayan Mukherjee,et al.  Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.

[25]  Alvy Ray Smith,et al.  Color gamut transform pairs , 1978, SIGGRAPH.

[26]  Alberto Del Bimbo,et al.  Retrieval of paintings using effects induced by color features , 1998, Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database.

[27]  Joyce H. Townsend.  Turner's Painting Techniques , 1993 .

[28]  J. Davenport.  Editor , 1960 .

[29]  Shih-Fu Chang,et al.  Image Retrieval: Current Techniques, Promising Directions, and Open Issues , 1999, J. Vis. Commun. Image Represent..

[30]  John Gage,et al.  Color and Meaning: Art, Science, and Symbolism , 2000 .

[31]  Adam L. Berger,et al.  ERROR-CORRECTING OUTPUT CODING FOR TEXT CLASSIFICATION , 1999 .

[32]  Rayid Ghani,et al.  Using Error-Correcting Codes for Text Classification , 2000, ICML.

[33]  Robert Sablatnig,et al.  Hierarchical classification of paintings using face- and brush stroke models , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[34]  S. Sathiya Keerthi,et al.  Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms , 2002, IEEE Trans. Neural Networks.

[35]  Vladimir Vapnik,et al.  The Nature of Statistical Learning , 1995 .

[36]  Nello Cristianini,et al.  Large Margin DAGs for Multiclass Classification , 1999, NIPS.

[37]  Rui Li,et al.  From Region Features to Semantic Labels: a Probabilistic Approach , 2003, MMM.

[38]  Magali Sarfatti Larson,et al.  Painting and Experience in Fifteenth Century Italy. , 1996 .

[39]  Ulrich H.-G. Kreßel,et al.  Pairwise classification and support vector machines , 1999 .

[40]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[41]  Patrick Haffner,et al.  Support vector machines for histogram-based image classification , 1999, IEEE Trans. Neural Networks.

[42]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[43]  Bernhard Schölkopf,et al.  Comparing support vector machines with Gaussian kernels to radial basis function classifiers , 1997, IEEE Trans. Signal Process..

[44]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[45]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[46]  D. Humphreys,et al.  Colour Science , 1969, Nature.

[48]  Chih-Jen Lin,et al.  A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.

[49]  Naohiro Ishii,et al.  Color, shape and impression keyword as attributes of paintings for information retrieval , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).