Research in music and artificial intelligence
ACM Computing Surveys (CSUR)
Aaron's code
A noniterative thinning algorithm
ACM Transactions on Mathematical Software (TOMS)
The role of emotion in believable agents
Communications of the ACM
Affective computing
Identification of Fork Points on the Skeletons of Handwritten Chinese Characters
IEEE Transactions on Pattern Analysis and Machine Intelligence
The METAFONTbook
A Shape Analysis Model with Applications to a Character Recognition System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Teaching to Write Japanese Characters using a Haptic Interface
HAPTICS '02 Proceedings of the 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
Skeleton Based Shape Matching and Retrieval
SMI '03 Proceedings of the Shape Modeling International 2003
Tutorial: A Survey of Stroke-Based Rendering
IEEE Computer Graphics and Applications
Automatic Generation of Artistic Chinese Calligraphy
IEEE Intelligent Systems
Animating Chinese paintings through stroke-based decomposition
ACM Transactions on Graphics (TOG)
Canonical Skeletons for Shape Matching
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Automatic generation of artistic chinese calligraphy
IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
Latent Style Model: Discovering writing styles for calligraphy works
Journal of Visual Communication and Image Representation
Style-consistency calligraphy synthesis system in digital library
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Chinese calligraphy specific style rendering system
Proceedings of the 10th annual joint conference on Digital libraries
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Our work links Chinese calligraphy to computer science through an integrated intelligence approach. We first extract strokes of existent calligraphy using a semi-automatic, two-phase mechanism: the first phase tries to do the best possible extraction using a combination of algorithmic techniques; the second phase presents an intelligent user interface to allow the user to provide input to the extraction process for the difficult cases such as those in highly random, cursive, or distorted styles. Having derived a parametric representation of calligraphy, we employ a supervised learning based method to explore the space of visually pleasing calligraphy. A numeric grading method for judging the beauty of calligraphy is then applied to the space. We integrate such a grading unit into an existent constraint-based reasoning system for calligraphy generation, which results in a significant enhancement in terms of visual quality in the automatically generated calligraphic characters. Finally, we construct an intelligent calligraphy tutoring system making use of the above. This work represents our first step towards understanding the human process of appreciating beauty through modeling the process with an integration of available AI techniques. More results and supplementary materials are provided at http://www.cs.hku.hk/~songhua/calligraphy.