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Animated construction of ink-wash paintings

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Published:24 November 2014Publication History

ABSTRACT

Chinese ink-wash painting is a unique and fascinating form of art. Revealing the drawing process of an ink-wash artwork is visually intriguing and useful for training of painting skills. Recording the sequences of strokes by camera during the creation of paintings is either laborious or even unavailable especially for some ancient paintings. In this work, we propose an effective solution for estimating an order given a number of 2D strokes extracted from ink-wash painting images (Figure 1). The understanding of art varies with people, so our objective is finding a reasonable solution that is plausible to human eyes, instead of searching for the best drawing sequence. We formulate the ordering of strokes as breadth first search on a graph encoding both the individual features of strokes (e.g., size, shade, position, etc.) and their spatial relationships. Compared with the work of recovering the drawing order of line artworks [Fu et al. 2011], our problem is more difficult since the art form of ink-wash painting is more complicated than line drawing.

References

  1. Fu, H., Zhou, S., Liu, L., and Mitra, N. J. 2011. Animated construction of line drawings. ACM Transactions on Graphics 30, 6 (Dec.), 133:1--133:10. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        • Published in

          cover image ACM Other conferences
          SA '14: SIGGRAPH Asia 2014 Posters
          November 2014
          47 pages
          ISBN:9781450327923
          DOI:10.1145/2668975

          Copyright © 2014 Owner/Author

          Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 24 November 2014

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          • research-article

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          Overall Acceptance Rate178of869submissions,20%

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