Bringing Pictorial Space to Life: computer techniques for the analysis of paintings

This paper explores the use of computer graphics and computer vision techniques in the history of art. The focus is on analysing the geometry of perspective paintings to learn about the perspectival skills of artists and explore the evolution of linear perspective in history. Algorithms for a systematic analysis of the twoand three-dimensional geometry of paintings are drawn from the work on “single-view reconstruction” and applied to interpreting works of art from the Italian Renaissance and later periods. Since a perspectival painting is not a photograph of an actual subject but an artificial construction subject to imaginative manipulation and inadvertent inaccuracies, the internal consistency of its geometry must be assessed before carrying out any geometric analysis. Some simple techniques to analyse the consistency and perspectival accuracy of the geometry of a painting are discussed. Moreover, this work presents new algorithms for generating new views of a painted scene or portions of it, analysing shapes and proportions of objects, filling in occluded areas, performing a complete threedimensional reconstruction of a painting and a rigorous analysis of possible reconstruction ambiguities. The validity of the techniques described here is demonstrated on a number of historical paintings and frescoes. Whenever possible, the computer-generated results are compared to those obtained by art historians through careful manual analysis. This research represents a further attempt to build a constructive dialogue between two very different disciplines: computer science and history of art. Despite their fundamental differences, science and art can learn and be enriched by each other’s procedures. A longer and more detailed version of this paper may be found in [5].

[1]  Andrew Zisserman,et al.  Planar grouping for automatic detection of vanishing lines and points , 2000, Image Vis. Comput..

[2]  Philip Steadman,et al.  Vermeer's Camera , 2001 .

[3]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  A. H.,et al.  The Science of Art , 1897, Nature.

[5]  Ken-ichi Anjyo,et al.  Tour into the picture: using a spidery mesh interface to make animation from a single image , 1997, SIGGRAPH.

[6]  Takeo Kanade,et al.  Recovery of the Three-Dimensional Shape of an Object from a Single View , 1981, Artif. Intell..

[7]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[8]  Jitendra Malik,et al.  Modeling and Rendering Architecture from Photographs: A hybrid geometry- and image-based approach , 1996, SIGGRAPH.

[9]  Li Zhang,et al.  Single view modeling of free-form scenes , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[10]  Antonio Criminisi,et al.  Shape from Texture: Homogeneity Revisited , 2000, BMVC.

[11]  Patricia Fara,et al.  Visualizations: The Nature Book of Art and Science , 2001 .

[12]  David Hockney,et al.  That's the Way I See It , 1993 .

[13]  Ian D. Reid,et al.  A plane measuring device , 1999, Image Vis. Comput..

[14]  J. G. Semple,et al.  Algebraic Projective Geometry , 1953 .

[15]  Catherine Caufield Masters of Illusion , 1996 .

[16]  Gunilla Borgefors,et al.  Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Andrew Zisserman,et al.  Shape from symmetry: detecting and exploiting symmetry in affine images , 1995, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences.

[18]  Zhengyou Zhang,et al.  New Measurements and Corner-Guidance for Curve Matching with Probabilistic Relaxation , 2002, International Journal of Computer Vision.

[19]  S. B. Kang,et al.  Reflections of Reality in Jan van Eyck and Robert Campin , 2004 .

[20]  H. Bülthoff,et al.  INTERACTION OF DIFFERENT MODULES IN DEPTH PERCEPTION. , 1987, ICCV 1987.

[21]  Marc De Mey Linear Perspective , 1992 .

[22]  Frédo Durand,et al.  A gentle introduction to bilateral filtering and its applications , 2007, SIGGRAPH Courses.

[23]  Sing Bing Kang,et al.  Depth Painting for Image-based Rendering Applications , 1999 .

[24]  Shree K. Nayar,et al.  Vision in bad weather , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[25]  della Francesca Piero,et al.  De prospectiva pingendi , 1984 .

[26]  Antonio Criminisi,et al.  Accurate Visual Metrology from Single and Multiple Uncalibrated Images , 2001, Distinguished Dissertations.

[27]  Daniel Menelly,et al.  Masters of Illusion. , 2004 .

[28]  S. P. Mudur,et al.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

[29]  Alexei A. Efros,et al.  Texture synthesis by non-parametric sampling , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[30]  J. V. Field,et al.  The Invention of Infinity: Mathematics and Art in the Renaissance , 1999 .

[31]  Cordelia Schmid,et al.  The Geometry and Matching of Curves in Multiple Views , 1998, ECCV.

[32]  Bronwen Brown Secret Knowledge: Rediscovering the Lost Techniques of the Old Masters , 2002 .

[33]  Luc Van Gool,et al.  Planar homologies as a basis for grouping and recognition , 1998, Image Vis. Comput..

[34]  H. Bülthoff,et al.  Does the brain know the physics of specular reflection? , 1990, Nature.