A generative model for handwritings based on enhanced feature desynchronization

Seiichi Uchida; Toru Sasaki; Feng Yaokai

doi:10.1109/ICDAR.2011.124

A generative model for handwritings based on enhanced feature desynchronization

Seiichi Uchida, Toru Sasaki, Feng Yaokai

Real world robotics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A new generative model of handwriting patterns is proposed for interpreting their deformations. The model is based on feature desynchronization, which is a coupling process of x and y coordinate features of different timings. By changing the timings to be coupled, the model can generate various deformed patterns from a single pattern. The model is further enhanced by incorporating an adaptive rotation at each timing for increasing the variety of deformed patterns. An important fact is that this enhanced desynchronization model can be interpreted intuitively as a deformation process in actual handwriting. Experimental results showed that the model can generate various handwriting patterns close to actual deformed patterns.

Original language	English
Title of host publication	Proceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011
Pages	589-593
Number of pages	5
DOIs	https://doi.org/10.1109/ICDAR.2011.124
Publication status	Published - Dec 2 2011
Event	11th International Conference on Document Analysis and Recognition, ICDAR 2011 - Beijing, China Duration: Sept 18 2011 → Sept 21 2011

Publication series

Name	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)	1520-5363

Other

Other	11th International Conference on Document Analysis and Recognition, ICDAR 2011
Country/Territory	China
City	Beijing
Period	9/18/11 → 9/21/11

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICDAR.2011.124

Cite this

Uchida, S., Sasaki, T., & Yaokai, F. (2011). A generative model for handwritings based on enhanced feature desynchronization. In Proceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011 (pp. 589-593). [6065379] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR). https://doi.org/10.1109/ICDAR.2011.124

A generative model for handwritings based on enhanced feature desynchronization. / Uchida, Seiichi; Sasaki, Toru; Yaokai, Feng.

Proceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011. 2011. p. 589-593 6065379 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Uchida, S, Sasaki, T & Yaokai, F 2011, A generative model for handwritings based on enhanced feature desynchronization. in Proceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011., 6065379, Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, pp. 589-593, 11th International Conference on Document Analysis and Recognition, ICDAR 2011, Beijing, China, 9/18/11. https://doi.org/10.1109/ICDAR.2011.124

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abstract = "A new generative model of handwriting patterns is proposed for interpreting their deformations. The model is based on feature desynchronization, which is a coupling process of x and y coordinate features of different timings. By changing the timings to be coupled, the model can generate various deformed patterns from a single pattern. The model is further enhanced by incorporating an adaptive rotation at each timing for increasing the variety of deformed patterns. An important fact is that this enhanced desynchronization model can be interpreted intuitively as a deformation process in actual handwriting. Experimental results showed that the model can generate various handwriting patterns close to actual deformed patterns.",

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A generative model for handwritings based on enhanced feature desynchronization

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All Science Journal Classification (ASJC) codes

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