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Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II

Research Article

Visual Nondestructive Rendering of 3D Animation Images Based on Large Data

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  • @INPROCEEDINGS{10.1007/978-3-030-67874-6_38,
        author={Yang Zhang and Xu Zhu},
        title={Visual Nondestructive Rendering of 3D Animation Images Based on Large Data},
        proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II},
        proceedings_a={ADHIP PART 2},
        year={2021},
        month={1},
        keywords={Big data Three-dimensional animation Image vision Non-destructive rendering},
        doi={10.1007/978-3-030-67874-6_38}
    }
    
  • Yang Zhang
    Xu Zhu
    Year: 2021
    Visual Nondestructive Rendering of 3D Animation Images Based on Large Data
    ADHIP PART 2
    Springer
    DOI: 10.1007/978-3-030-67874-6_38
Yang Zhang1, Xu Zhu1,*
  • 1: Liaoning Communication University
*Contact email: xuenne@163.com

Abstract

In the visual non-destructive rendering of three-dimensional animation images, the traditional visual non-destructive rendering method is slow, so a visual non-destructive rendering method of three-dimensional animation images based on large data is proposed. The theoretical model of pixel-by-pixel time-domain denoising process is used to denoise, and GPU is used to achieve time-domain consistent processing according to the denoising results. The non-linear Kuwahara filter is used to smooth the three-dimensional animation image, and the first-order differential operator is used to highlight the dramatically changing pixels in the image, so as to detect the edge of the image. After obtaining the distinct contour of the three-dimensional animation image, the non-destructive rendering of the three-dimensional animation image vision is realized. In order to verify the effectiveness of this method, the average rendering speed of the proposed method is 83.2%, which is significantly higher than that of the traditional method. The experimental results show that the average rendering speed of this method is the highest, the image rendering effect of this method is better, and the effectiveness of this method is verified.

Keywords
Big data Three-dimensional animation Image vision Non-destructive rendering
Published
2021-01-29
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67874-6_38
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