Research on the Application of Computer Big Data Technology in Artistic Innovation Design
DOI:
https://doi.org/10.54097/hset.v1i.423Keywords:
Computer, big data technology, Performance innovation, Projection decomposition, Artistic innovationAbstract
This article uses computer big data methods to simulate and model the emergence of creative innovations in performances. Use computer symbolization theory and computer recognition technology to express different creative elements of performing arts on a computer. According to the characteristics of performing arts, we realize the computer modelling method based on projection decomposition and realize the segmentation and reorganization of video data with parallel and multi-core fast algorithms. The results show that the system can effectively improve the practicability, reliability and efficiency of the stage design.
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Han Xiong. Research on the Art of Painting Creation in the Era of Big Data——Comment on Art Education in the Era of Big Data. Science and Technology Management Research,462(20) (2020) 273-273.
Song Quanchang. Design of Hierarchical Planning System for Plant Landscape Space under Big Data. Modern Electronic Technology, 43(10) (2020) 4-11.
Yin Xiujuan, Han Pugeng. A rational reflection on artificial intelligence "art creation". Hubei Social Sciences, 10(2) (2020) 47-52.
Wu Wenhan. On the Discourse Practice of Artificial Intelligence and the Reflection on Art Aesthetics. Modern Communication, 42(4) (2020) 100-105.
Li Qiansheng. Beyond Visualization: Rethinking the Teaching of Information Visualization Courses in Art Schools. Decoration, 323(3) (2020) 60-63.
Cui Yan. Application and Thinking of Public Opinion Big Data in the Film Industry. Contemporary Film, 278(5) (2019) 72-76.
Bi Ya, Yuan Huiqun, Chu Yeping, et al. Resource multi-level intelligent rent-seeking and matching strategy and value creation based on public service platform in big data environment. Computer Science, 46(2) (2019) 51-58.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
