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Learning style translation for the lines of a drawing
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Source ACM Transactions on Graphics (TOG) archive
Volume 22 ,  Issue 1  (January 2003) table of contents
Pages: 33 - 46  
Year of Publication: 2003
ISSN:0730-0301
Authors
William T. Freeman  Mitsubishi Electric Research Labs and MIT Artificial Intelligence Laboratory, Cambridge, MA
Joshua B. Tenenbaum  MIT Brain and Cognitive Sciences Department
Egon C. Pasztor  Mitsubishi Electric Research Labs and MIT Media Laboratory
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 11,   Downloads (12 Months): 52,   Citation Count: 5
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ABSTRACT

We present an example-based method for translating line drawings into different styles. We fit each line as a linear combination of similar lines in a training set, and interpolate between the corresponding training examples in the output style. The synthesized lines preserve the desired stylistic features of the output style.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Borgman, H. 1977. Drawing in ink. Watson--Guptill, New York.
 
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Cleveland, W. S. and Loader, C. 1995. Smoothing by Local Regression: Principles and Methods. Springer-Verlag, New York.
 
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Hamel, J. and Strothotte, T. 1999. Capturing and re-using rendition styles for non-photorealistic rendering. Comput. Graph. Forum. 18, 173--182.
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Omohundro, S. M. 1995. Family discovery. Adv. Neural Inf. Process. Syst. 8, 402--408.
 
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Simard, P. Y., Cun, Y. L., and Denker, J. S. 1994. Memory-based character recognition using a transformation invariant metric. In Proceedings of the IEEE Twelfth International Conference on Pattern Recognition, vol. 2 (Jerusalem), 262--267.
 
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Collaborative Colleagues:
William T. Freeman: colleagues
Joshua B. Tenenbaum: colleagues
Egon C. Pasztor: colleagues