Digital Inheritance of POPF Based on Image Database and Identification Model

Authors

  • Guancan Yang School of Information Resource Management, Renmin University of China, Beijing, China
  • Huilin Zhang School of Information Resource Management, Renmin University of China, Beijing, China
  • Xiaomei Zhang School of Information Resource Management, Renmin University of China, Beijing, China
  • Yue Yu School of Information Resource Management, Renmin University of China, Beijing, China
  • Jie Yang School of Information Resource Management, Renmin University of China, Beijing, China

DOI:

https://doi.org/10.55630/dipp.2019.9.33

Keywords:

Pecking Opera Painted Faces (POPF), Intangible Cultural Heritage, Image Database, Identification Model

Abstract

Pecking Opera Painted Faces (POPF) is a Chinese intangible cultural heritage full of aesthetic value. However, their cultural connotations become less known in modern society. It is therefor, necessary to make public easily understand unique cultural connotation and aesthetic value of POPF. In this project, we built a POPF image database based on the image classification model, with the aim to better showcase POPF. The images are classified into multiple categories according to the traditional connotation patterns. By using the MLP (Multilayer Perceptrons) algorithm classifier, the classification accuracy of model has approached 70%. Using those tools, the uncertainty of information about images of POPF can be reduced appreciably, and would benefit the innovation of derivatives around POPF.

References

Di, C., & Kang, S. (2010). Study on the application of Peking Opera sign in the creation process of character animation under semiotics. IEEE International Conference on Computer-aided Industrial Design & Conceptual Design. IEEE.

Ding, W., Jinsheng, K., & Shengfeng, Q. (2014). The significance of information visualization based on the symbolic semantics of Peking Opera Painted Faces (POPF). Twentieth International Conference on Automation & Computing, ICAC 2014. Bedfordshire, UK.

Peng, Z., Qing, Z., & Zhiqiang, W. (2017). Research on classification and recognition of Peking opera facial images based on SIFT features and support vector machine. Second International Conference on Electromechanical Control Technology and Transportation, ICECTT 2017. Zhuhai, China.

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Published

2019-09-13

How to Cite

Yang, G., Zhang, H., Zhang, X., Yu, Y., & Yang, J. (2019). Digital Inheritance of POPF Based on Image Database and Identification Model. Digital Presentation and Preservation of Cultural and Scientific Heritage, 9, 315–322. https://doi.org/10.55630/dipp.2019.9.33