Abstract
This paper presents a novel approach for online multi-strokes composite sketchy shape recognition based on Bayesian Networks. By means of the definition of a double-level Bayesian networks, a classifier is designed to model the intrinsic temporal orders among the strokes effectively, where a sketchy shape is modeled with the relationships not only between a stroke and its neighbouring strokes, but also between a stroke and all of its subsequence.. The drawing-style tree is then adopted to capture the users’ accustomed drawing styles and simplify the training and recognition of Bayesian network classifier. The experiments prove both effectiveness and efficiency of the proposed method.
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Sun, Z., Liu, J.: Informal user interface for graphical computing. In: Tao, J., Tan, T., Picard, R.W. (eds.) ACII 2005. LNCS, vol. 3784, pp. 675–682. Springer, Heidelberg (2005)
Landay, J.A., Myers, B.A.: Sketching Interfaces: toward more human interface design. IEEE Computer 34(3), 56–64 (2001)
Newman, M.W., James, L., Hong, J.I., et al.: DENIM: An informal web site design tool inspired by observations of practice. In: HCI, vol. 18, pp. 259–324 (2003)
Fonseca, M.J., Pimentel, C., Jorge, J.A.: CALI - an online scribble recognizer for calligraphic interfaces. In: AAAI Spring Symposium on Sketch Understanding, pp. 51–58. AAAI Press, Menlo Park (2002)
Calhoun, C., Thomas, F.S., Kurtoglu, T., et al.: Recognizing multi-stroke symbols. In: AAAI Spring Symposium on Sketch Understanding, pp. 15–23. AAAI Press, Menlo Park (2002)
Xu, X., Sun, Z., et al.: An online composite graphics recognition approach based on matching of spatial relation graphs. IIDAR 7(1), 44–55 (2004)
Sun, Z., Liu, W., Peng, B., et al.: User adaptation for online sketchy shape recognition. In: Lladós, J., Kwon, Y.-B. (eds.) GREC 2003. LNCS, vol. 3088, pp. 305–316. Springer, Heidelberg (2004)
Sun, Z., Zhang, L., Tang, E.: An incremental learning algorithm based on SVM for online sketchy shape recognition. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3610, pp. 655–659. Springer, Heidelberg (2005)
Sezgin, T.M., Davis, R.: HMM-Based Efficient Sketch Recognition. In: Proceedings of the 10th international conference on IUI, San Diego, California, USA (January 2005)
Sun, Z., Jiang, W., Sun, J.: Adaptive Online Multi-Stroke Sketch Recognition based on Hidden Markov Model. LNCS (LNAI), vol. 3784, pp. 948–957. Springer, Heidelberg (2005)
Friedman, N., Geiger, D., Goldszmidt, M.: Bayesian network classifiers. In: Machine learning, vol. 29(2-3), pp. 131–163. Kluwer Academic Publishers, Hingham (1997)
Sung-Jung, C., Kim Jin, H.: Bayesian network modeling of Hangul characters for online handwriting recognition. In: Proceedings of IDAR 2003, pp. 207–211 (2003)
Alvarado, C., Davis, R.: Dynamically Constructed Bayesian Networks for Sketch Understanding. In: Proceedings of IJCAI 2005, Edinburgh, Scotland (2005)
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Sun, Z., Zhang, L., Zhang, B. (2006). Online Composite Sketchy Shape Recognition Based on Bayesian Networks. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_63
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DOI: https://doi.org/10.1007/11881223_63
Publisher Name: Springer, Berlin, Heidelberg
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