“Learning Hatching for Pen-and-Ink Illustration of Surfaces” by Kalogerakis, Nowrouzezahrai, Breslav and Hertzmann

  • ©Evangelos Kalogerakis, Derek Nowrouzezahrai, Simon Breslav, and Aaron Hertzmann

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Title:

    Learning Hatching for Pen-and-Ink Illustration of Surfaces

Presenter(s)/Author(s):



Abstract:


    This article presents an algorithm for learning hatching styles from line drawings. An artist draws a single hatching illustration of a 3D object. Her strokes are analyzed to extract the following per-pixel properties: hatching level (hatching, cross-hatching, or no strokes), stroke orientation, spacing, intensity, length, and thickness. A mapping is learned from input geometric, contextual, and shading features of the 3D object to these hatching properties, using classification, regression, and clustering techniques. Then, a new illustration can be generated in the artist’s style, as follows. First, given a new view of a 3D object, the learned mapping is applied to synthesize target stroke properties for each pixel. A new illustration is then generated by synthesizing hatching strokes according to the target properties.

References:


    Arvo, J. 1995. Applications of irradiance tensors to the simulation of non-lambertian phenomena. In Proceedings of the SIGGRAPH Conference. 335–342. Google ScholarDigital Library
    Barla, P., Breslav, S., Thollot, J., Sillion, F., and Markosian, L. 2006. Stroke pattern analysis and synthesis. Comput. Graph. Forum 25, 3.Google ScholarCross Ref
    Belongie, S., Malik, J., and Puzicha, J. 2002. Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24, 4. Google ScholarDigital Library
    Bishop, C. M. 2006. Pattern Recognition and Machine Learning. Springer. Google ScholarDigital Library
    Boykov, Y., Veksler, O., and Zabih, R. 2001. Fast approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal. Mach. Intell. 23, 11. Google ScholarDigital Library
    Cole, F., Golovinskiy, A., Limpaecher, A., Barros, H. S., Finkelstein, A., Funkhouser, T., and Rusinkiewicz, S. 2008. Where do people draw lines? ACM Trans. Graph. 27, 3. Google ScholarDigital Library
    DeCarlo, D. and Rusinkiewicz, S. 2007. Highlight lines for conveying shape. In Proceedings of the NPAR Conference. Google ScholarDigital Library
    Elber, G. 1998. Line art illustrations of parametric and implicit forms. IEEE Trans. Vis. Comput. Graph. 4, 1, 71–81. Google ScholarDigital Library
    Freeman, W. T., Tenenbaum, J., and Pasztor, E. 2003. Learning style translation for the lines of a drawing. ACM Trans. Graph. 22, 1, 33–46. Google ScholarDigital Library
    Friedman, J., Hastie, T., and Tibshirani, R. 2000. Additive logistic regression: A statistical view of boosting. Ann. Statist. 38, 2.Google Scholar
    Goodwin, T., Vollick, I., and Hertzmann, A. 2007. Isophote distance: A shading approach to artistic stroke thickness. In Proceedings of the NPAR Conference. 53–62. Google ScholarDigital Library
    Guptill, A. L. 1997. Rendering in Pen and Ink, S. E. Meyer, Ed., Watson-Guptill.Google Scholar
    Hamel, J. and Strothotte, T. 1999. Capturing and re-using rendition styles for non-photorealistic rendering. Comput. Graph. Forum 18, 3, 173–182.Google ScholarCross Ref
    Hertzmann, A., Jacobs, C. E., Oliver, N., Curless, B., and Salesin, D. H. 2001. Image analogies. In Proceedings of the SIGGRAPH Conference. Google ScholarDigital Library
    Hertzmann, A., Oliver, N., Curless, B., and Seitz, S. M. 2002. Curve analogies. In Proceedings of the EGWR Conference. Google ScholarDigital Library
    Hertzmann, A. and Zorin, D. 2000. Illustrating smooth surfaces. In Proceedings of the SIGGRAPH Conference. 517–526. Google ScholarDigital Library
    Hilaga, M., Shinagawa, Y., Kohmura, T., and Kunii, T. L. 2001. Topology matching for fully automatic similarity estimation of 3d shapes. In Proceedings of the SIGGRAPH Conference. Google ScholarDigital Library
    Jodoin, P.-M., Epstein, E., Granger-Piché, M., and Ostromoukhov, V. 2002. Hatching by example: A statistical approach. In Proceedings of the NPAR Conference. 29–36. Google ScholarDigital Library
    Jordan, M. I. and Jacobs, R. A. 1994. Hierarchical mixtures of experts and the em algorithm. Neur. Comput. 6, 181–214. Google ScholarDigital Library
    Judd, T., Durand, F., and Adelson, E. 2007. Apparent ridges for line drawing. ACM Trans. Graph. 26, 3. Google ScholarDigital Library
    Kalnins, R., Markosian, L., Meier, B., Kowalski, M., Lee, J., Davidson, P., Webb, M., Hughes, J., and Finkelstein, A. 2002. WYSIWYG NPR: Drawing strokes directly on 3D models. In Proceedings of the SIGGRAPH Conference. 755–762. Google ScholarDigital Library
    Kalogerakis, E., Hertzmann, A., and Singh, K. 2010. Learning 3d mesh segmentation and labeling. ACM Trans. Graph. 29, 3. Google ScholarDigital Library
    Kalogerakis, E., Nowrouzezahrai, D., Simari, P., McCrae, J., Hertzmann, A., and Singh, K. 2009. Data-Driven curvature for real-time line drawing of dynamic scenes. ACM Trans. Graph. 28, 1. Google ScholarDigital Library
    Kim, S., Maciejewski, R., Isenberg, T., Andrews, W. M., Chen, W., Sousa, M. C., and Ebert, D. S. 2009. Stippling by example. In Proceedings of the NPAR Conference. Google ScholarDigital Library
    Kim, S., Woo, I., Maciejewski, R., and Ebert, D. S. 2010. Automated hedcut illustration using isophotes. In Proceedings of the Smart Graphics Conference. Google ScholarDigital Library
    Kim, Y., Yu, J., Yu, X., and Lee, S. 2008. Line-Art illustration of dynamic and specular surfaces. ACM Trans. Graphics. Google ScholarDigital Library
    Liu, R. F., Zhang, H., Shamir, A., and Cohen-Or, D. 2009. A part-aware surface metric for shape analysis. Comput. Graph. Forum 28, 2.Google ScholarCross Ref
    Lum, E. B. and Ma, K.-L. 2005. Expressive line selection by example. Vis. Comput. 21, 8, 811–820.Google ScholarCross Ref
    Mertens, T., Kautz, J., Chen, J., Bekaert, P., and Durand., F. 2006. Texture transfer using geometry correlation. In Proceedings of the EGSR Conference. Google ScholarDigital Library
    Palacios, J. and Zhang, E. 2007. Rotational symmetry field design on surfaces. ACM Trans. Graph. Google ScholarDigital Library
    Praun, E., Hoppe, H., Webb, M., and Finkelstein, A. 2001. Real-Time Hatching. In Proceedings of the SIGGRAPH Conference. Google ScholarDigital Library
    Rusinkiewicz, S. and DeCarlo, D. 2007. rtsc library. http://www.cs. princeton.edu/gfx/proj/sugcon/.Google Scholar
    Saito, T. and Takahashi, T. 1990. Comprehensible rendering of 3-D shapes. In Proceedings of the SIGGRAPH Conference. 197–206. Google ScholarDigital Library
    Salisbury, M. P., Anderson, S. E., Barzel, R., and Salesin, D. H. 1994. Interactive pen-and-ink illustration. In Proceedings of the SIGGRAPH Conference. 101–108. Google ScholarDigital Library
    Shapira, L., Shalom, S., Shamir, A., Zhang, R. H., and Cohen-Or, D. 2010. Contextual part analogies in 3D objects. Int. J. Comput. Vis. Google ScholarDigital Library
    Shotton, J., Johnson, M., and Cipolla, R. 2008. Semantic texton forests for image categorization and segmentation. In Proceedings of the CVPR Conference.Google Scholar
    Shotton, J., Winn, J., Rother, C., and Criminisi, A. 2009. Textonboost for image understanding: Multi-Class object recognition and segmentation by jointly modeling texture, layout, and context. Int. J. Comput. Vis. 81, 1. Google ScholarDigital Library
    Simari, P., Kalogerakis, E., and Singh, K. 2006. Folding meshes: Hierarchical mesh segmentation based on planar symmetry. In Proceedings of the SGP Conference. Google ScholarDigital Library
    Singh, M. and Schaefer, S. 2010. Suggestive hatching. In Proceedings of the Computational Aesthetics Conference. Google ScholarDigital Library
    Sloan, P.-P., Kautz, J., and Snyder, J. 2002. Precomputed radiance transfer for real-time rendering in dynamic, low-frequency lighting environments. In Proceedings of the SIGGRAPH Conference. 527–536. Google ScholarDigital Library
    Torralba, A., Murphy, K. P., and Freeman, W. T. 2007. Sharing visual features for multiclass and multiview object detection. IEEE Trans. Pattern Anal. Mach. Intell. 29, 5. Google ScholarDigital Library
    Tu, Z. 2008. Auto-context and its application to high-level vision tasks. In Proceedings of the CVPR Conference.Google Scholar
    Turk, G. and Banks, D. 1996. Image-Guided streamline placement. In Proceedings of the SIGGRAPH Confernce. Google ScholarDigital Library
    Wagstaff, K., Cardie, C., Rogers, S., and Schrödl, S. 2001. Constrained k-means clustering with background knowledge. In Proceedings of the ICML Conference. Google ScholarDigital Library
    Winkenbach, G. and Salesin, D. 1994. Computer-Generated pen-and-ink illustration. In Proceedings of the SIGGRAPH Conference. 91–100. Google ScholarDigital Library
    Winkenbach, G. and Salesin, D. 1996. Rendering parametric surfaces in pen and ink. In Proceedings of the SIGGRAPH Conference. 469–476. Google ScholarDigital Library
    Zemel, R. and Pitassi, T. 2001. A gradient-based boosting algorithm for regression problems. In Proceedings of the Conference on Neural Information Processing Systems.Google Scholar
    Zeng, K., Zhao, M., Xiong, C., and Zhu, S.-C. 2009. From image parsing to painterly rendering. ACM Trans. Graph. 29. Google ScholarDigital Library


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