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ABSTRACT
Freehand sketching is a natural and powerful means of interpersonal communication. But to date, it still cannot be supported effectively by human-computer interface. In this paper, we propose a robust method for sketch recognition. It uses mean shift, a nonparametric technique which can delineate arbitrarily shaped clusters, as a pre-process to analyze the direction-curvature joint space and suppress the severe noise of sketched strokes. Furthermore, it combines the vertex detection and primitive shape approximation into a unified and incremental procedure which, by fully utilizing the visual features, can handle hybrid and smooth curves gracefully. Our method does not rely on any domain-specific knowledge, and therefore it can be easily integrated with other high-level applications
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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Hammond, T., and Davis, R. Tahuti: A Sketch Recognition System for UML Class Diagrams. AAAI Spring Symposium on Sketch Understanding, 2002.
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Takeo Igarashi , Satoshi Matsuoka , Sachiko Kawachiya , Hidehiko Tanaka, Interactive beautification: a technique for rapid geometric design, Proceedings of the 10th annual ACM symposium on User interface software and technology, p.105-114, October 14-17, 1997, Banff, Alberta, Canada
[doi> 10.1145/263407.263525]
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